SAIPA’s annual Project Achiever programme supports young and aspiring Professional Accountants (SA) to advance their accountancy career, which for many is the fulfilment of a lifelong dream. In this series, SAIPA introduces you to some of the accomplished Project Achiever alumni and project facilitators to inspire both present and future members about the world of possibility of being a SAIPA member.
1. Tell us about yourself and your career thus far.
I’m from Pietermaritzburg, KZN originally, and currently live and work in Durban. During my studies, I specialised in both management accounting and taxation. I have been a lecturer at Mangosuthu University of Technology (MUT) for around 17 years, since 2006. As a senior lecturer at MUT, my primary area of teaching is taxation. However, I have also previously taught courses in management accounting. Before that, I lectured at Durban University of Technology. I am also a member of the Finance and Investment Committee on the MUT Council.
2. What attracted you to academia?
In the early stages of my career, I wasn’t necessarily attracted to academia per se. Rather, I’ve always been interested in community service. I’ve always seen myself as both an activist and a community builder. This is something that I would have done in one form or other. When an opportunity was presented for me to lecture young people, I took it with both hands because I have always known that education is a great tool to positively impact people’s lives, particularly those from underprivileged backgrounds.
3. Tell us about how you become involved with Project Achiever.
I have been a facilitator for the SAIPA Project Achiever programme since its inception in 2015. I was recommended to join the programme by the then Head of Department for accounting at Mangosuthu University of Technology. She was initially chosen to be a facilitator but couldn’t take on the role at the time – so the opportunity became available for me and I was happy to oblige! At the time, SAIPA was looking for someone to facilitate the taxation and management accounting sessions, which aligned perfectly with my expertise. In the beginning stages of the program it was more regional in nature, but now it has grown to be nationwide.
4. What impact is Project Achiever having on those who come through the programme?
All of us as a collective – SAIPA, the project facilitators, and everyone involved in the programme at various levels – we are truly making a contribution in developing and preparing these young minds to not only become Professional Accountants, but to also be ready for the world of work. We are equipping them with skills to be first and foremost professionals who have the capability to use their knowledge to make a difference to organisations and the wider society. The programme is not limited to only developing accountancy skills – the Project Achiever programme is structured around developing a holistic professional who’s going to be able to step into any organisation in any place and be able to analyse the situation and provide necessary advisory. We are hopefully making an impact in creating a cohort of Professional Accountants who are critical thinkers and who will do their part in building communities and societies.
5. Who has had the biggest influence on your life?
Honestly, I can’t name one person. My life journey has been the epitome of the expression ‘it takes a village to raise a child’. My grandmother, parents, aunts, sisters, and a lot of my friends have been instrumental in supporting me towards reaching my goals. If I have to single out one person, I would say that I have always looked up to my father. I even feel emotional as I think about him. He is someone who has inspired me throughout my life.
6. What is your philosophy of life?
I believe in doing good, wherever you can and however you can. I think everybody has the potential to make a positive impact on the lives of others and we have a duty to live up to this potential.
7. What are some of your interests/passions, outside of the office?
I play football with my friends from time to time. I am also a political activist. Those are the two things that I like to do. So, if I’m not reading a book and debating with people or involved in some community activity, I’ll be playing football. I come from a very poor area and when I got to university, I was introduced to the writings of Robert Sobukwe. From then on, I found myself interested in community activism that is aimed at uplifting the marginalized, particularly in African communities.
8. What do you consider the biggest opportunity you received thus far?
I think I’m a fortunate guy – I’ve received too many to count. But at the top of my head, I think the Project Achiever programme has been an amazing opportunity to have a positive impact in people’s lives. The programme has also made an impact in helping to diversify the profession, which is something that is dear to my heart. As each year passes, we are seeing more black people and women becoming Professional Accountants. It’s pleasing to me that, through the programme, I get to play a role in setting previously marginalised people on a path to career success.
9. What is your hope for the future of the Project Achiever Programme?
The government has expressed many times that accountancy skills are scarce in South Africa. Through the Project Achiever programme, I hope we can have a positive impact in closing that skills gap by developing the necessary human capital for the future growth of our country. I hope that Project Achiever will have the resources (both human and financial) to continue to grow and take on more students so the impact of the programme can expand throughout South Africa.
Two-thirds of HR leaders globally say the labor shortage is getting worse. Talent acquisition teams are struggling to get enough qualified candidates in the pipeline to reach their hiring goals.
In the United States, for example, there are nearly two open jobs for every unemployed job seeker and 61% of U.S. business leaders say it’s challenging to attract top talent. Job seekers have many opportunities available to them, creating a lot of competition in the talent market.
Recruiting passive candidates can help.
Passive candidates are workers who aren’t actively looking for a new job, but may be open to the right role. A recent study by Achievers estimates that passive candidates account for 39% of the talent pool. This represents an enormous opportunity for employers to fill their talent pipeline with candidates who aren’t actively considering other roles.
Here’s how to maximize this recruitment strategy for the best results:
Start with an intake meeting
Efficient recruitment processes often begin with a hiring manager kickoff meeting to learn about the role and ideal candidate profile. (An intake form will also suffice if you prefer to work asynchronously or have a longstanding relationship with the hiring manager.) Get an understanding of required and desired qualifications and what can be learned on the job.
Challenge any unnecessary job requirements such as a degree or specific company background that may exclude otherwise qualified candidates. This is a common practice in a tight labor market; employers reduced degree requirements for 46% of middle-skill positions and 31% of high-skill positions when hiring was extremely competitive between 2017 and 2019.
Take time during your intake meeting to source a few candidates with your hiring manager so you can demonstrate what the talent pool looks like and get detailed feedback on candidates. Show how adding or removing qualifications can change the makeup of the talent pool so you can fine-tune your search and uncover the best candidates.
Proactively source passive candidates
Job postings only yield active job seekers, which is a fraction of job candidates available. Proactively sourcing talent will help you tap into more of the talent market to ensure you have a highly qualified and diverse talent pipeline.
Effective candidate sourcing channels include:
Recruiting tools. Online sourcing platforms like LinkedIn Recruiter can help your talent acquisition team quickly identify and engage skilled candidates for your open positions.
Your applicant tracking system. Search through your existing candidate database, paying particular attention to Silver Medalists and candidates you have an existing relationship with.
Employee referrals. An employee referral program is a great way to uncover candidates who are already connected to your team members, making them more likely to engage.
Internal talent. Considering current employees for your open roles can help you fill roles faster, while enabling career growth and improving retention.
Company alumni. Your former employees have gone on to learn new skills and gain new experiences. Why not bring them back as boomerang hires?
Professional associations. Get your team involved in professional associations so you can leverage the association’s events, directories, and communities.
Social media platforms. Leverage your network and participate in community conversations to identify and engage talent.
Conferences. Conference attendees have committed to growing in their field and speakers are often subject matter experts. You may also find talented sales and marketing professionals on the Expo floor, as well as PR professionals covering the event.
Write engaging candidate outreach
Passive candidates aren’t looking for new opportunities. You need to capture these candidates’ attention and convince them to consider your organization. A well-crafted outreach message can make all the difference in starting meaningful conversations and enticing passive candidates.
Craft a short, catchy subject line. Talented candidates are usually inundated with emails. A message with the subject line “job opening for X” isn’t likely to elicit a view — let alone a response. Instead, try pointing out a shared connection or personal interest to get the candidate’s attention and tempt them to read your message.
Name drop. Candidates are 46% more likely to accept an InMail if they're already connected to someone at your company. Use employee connections to your advantage by mentioning them by name in your outreach.
Personalize your message. LinkedIn data shows that personalized InMails perform about 15% better than ones sent in bulk. Show that you did your research by mentioning one of the candidate’s skills, interests, or accomplishments that stood out to you.
Share “what’s in it for me?” If your candidate isn’t looking for a new role, what can you offer to help them consider yours? It’s hard to know what would appeal most to each candidate, but LinkedIn data shows that work-life balance, compensation, benefits, colleagues, and company culture are a great place to start.
Share next steps. Conclude your message with a call to action that encourages your candidate to respond. Sharing your calendar or asking the candidate to offer a few time slots they’re available to chat can help you get a response.
Keep it brief. There’s so much you want to cover in your candidate outreach message, but be careful not to overdo it. LinkedIn data shows that InMails between 200 and 400 characters are 16% more likely to receive a response. Stick to the high-level details that entice your passive candidates to respond and learn more about your opportunity.
Have a casual conversation
Have a quick phone call, video chat, or a coffee meetup with your passive candidate to explore whether your opportunity could be a good fit and to sell them on pursuing it.
It’s important to start this conversation by listening so you can tailor your talking points to the candidate’s specific wants and needs. Learn why your candidate agreed to chat with you and what they would need to consider leaving their current employer.
For example, if your candidate is interested in career growth, you should focus the conversation on your L&D program and share career paths that your current employees have taken. If your candidate is interested in work-life balance, you should share your flexible work options like remote work, flex hours, and paid time off.
Tailoring your conversation in this way can help you sell the candidate on your opportunity so they feel it’s worth their time and energy to continue with your recruitment process.
Even if the candidate isn’t ready to make a move, take this opportunity to build a relationship with them. Find out what’s holding them back so that you can reach out again when the timing might be better.
For example, if your candidate is waiting to launch a major project at work or reaching some big milestones in their personal life, you might reach out in six months to a year to follow up. Or if your candidate just started a new job, you might reach out in a year or two to see how it’s going and reiterate your interest in having them join your team.
Simplify your candidate evaluation process
Once you’ve identified and engaged passive candidates, be careful not to lose them to a clunky evaluation process. Passive candidates aren’t necessarily looking for a new role and won’t waste their valuable time on processes that take too long, require too many steps, or put their current job at risk.
Simplify your evaluation process, including your:
Application process. Passive candidates don’t typically have updated resumes or the patience to complete a tedious application. Simplify your application process by eliminating unnecessary steps. For example, can you use the candidate’s LinkedIn profile in lieu of a resume or to prefill your job application?
Interview process. Passive job seekers don’t want to take excessive time away from work to complete your interview process. Consider how you can make it effective, but brief. For example, leverage video interviews to eliminate travel time, remove unnecessary interviews, and shorten your skills assessment.
Reference checks. Employed candidates aren’t likely to offer a current manager or colleague for reference checks. Candidates may also hesitate to provide former contacts if they believe it would jeopardize their current job. Be flexible with the type of references you request, considering past managers, peers, direct reports, instructors, classmates, freelance clients, and mentors.
Any changes made to your evaluation process should be made for all job seekers. This will help ensure a fair recruitment process — and it can help you keep your most in-demand active candidates engaged in your process as well.
Final thoughts: Continue talent pipelining for future roles
The typical hiring process yields a single new employee, leaving the rest of your high-quality candidates without a job offer. Make sure you provide each of them with a positive candidate experience so they’ll consider future opportunities with your company.
Build-long term relationships with your candidates by keeping in touch periodically. For example, connect with your candidates on LinkedIn so you can engage with their content, congratulate them on birthdays, and check in around work anniversaries. When a new opportunity within your organization opens up, you’ll have a talent pipeline full of potential candidates ready to go.
This topic has been on my mind for years. I have been steering content managers to take a more human approach when it comes to generating content for social media. Of course, these content managers (mostly) do not have a marketing degree. Most of them are the owners’ wives (yes, gender stereotyping), the personal assistant or someone in sales who suddenly was given a new unpaid role. Sadly, it goes to the so-called young person because s/he is tech-savvy.
SPOILER ALERT: You do not need a young person doing your social media. You need someone who can write.
Creative writing skills is going to help your business-content-audience connect. And this is the real gem of social media content development: connection.
During this time of COVID-19, people have a deep desire to connect. It could be a phone call or screaming “hello” to the neighbours. I have been running daily marketing webinars to support businesses. It was amazing how many business owners attend just to connect with people outside their homes (especially during SA Lockdown).
Human connection is strengthened during traumatic events. My partner and I were in a horrid 4x4 accident in Namibia over 2 years ago. We could have easily become angry or even resentful during that time that we were stuck in the middle of nowhere. Instead, the experience brought us closer and solidified our relationship. We are now happily married.
The human connections in your business will solidify and create your champions.
Let’s get back to how we develop connections through marketing. I know this might feel unauthentic if you are not this kind of person but right now, in business, we need to hustle with all the skills:
Re-connection
How often do you reconnect with your current or past clients? I often pick up the phone and call each one – just to find out how they are. No selling. We may chat about business or life events. Either way, a deep connection is made every time we talk.
It is your time to shine
It is time to put you at the forefront of your business. Show your face! Connecting with your audience through video (especially Live) will help people experience your in-store friendliness from the comfort of their home. Don’t worry that you may not have the right equipment or you haven’t received camera lessons – just do it. The more video content you produce, the easier it will get. Personally, I don’t mind seeing those imperfect moments. It makes the experience a lot more human. There is a Cape Town-based wine journalist, @capewinelover who recently started doing live wine tastings every night at 6pm. He has now created a rapport with his audience as well as wine estates that will last beyond lockdown.
Get personal
Open your content up to include stories of your personal experience. It needs to be relevant to the business otherwise it is just another story. Talk about why you started this business, what problem did you want to solve and what has the impact been?
Soften your tone
Social media is social by nature. The words and tone we use here need to be softer and more conversational. It should still be on-brand – just a little more inviting.
No hard-selling
If we assume that everyone knows what they want and values freedom of choice, then hard selling will never work. In fact, it is a turn-off and can make a customer sceptical. Why are you trying so hard?
No jargon
The days of confusing people with fancy jargon are over. People have a thirst of knowledge but more so, understanding. Talk to your audience about your products or services as if you are explaining it to your grandmother. You wouldn’t want to confuse Gran, would you?
Focus on experience
There are many ways businesses can still use social media without hard selling. My favourite way is focusing on experience. I know that the tourism industry has taken a huge knock this quarter but there is no reason to stop your marketing. You can still post virtual experiences, showcase tours that you have done or ask people to share their favourite holiday destination or activity.
Create relatable content
Your social media strategy should always remind you to create relatable content. Think about what your business does and match what you think your audience wants to hear right now. Rouge Day Spa in Kenilworth and Constantia started creating content around home treatments, for example how to do a Gelish soak-off. This is smart because even though their customers will now know how to DIY-it, most of them will still book a treatment post-lockdown.
The main point I want you to remember: This is not the time to stop marketing. Do not disappear from existence. You need to stay on top of people’s minds when the curtain is lifted again. This is the time to connect with our future champions in the closest human way possible.
All these tips I have been sharing for the last 10 years of digital marketing. It is now imperative that we implement these in our digital strategy going forward.
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Nowadays, a deviation from full-time, permanent jobs with one single employer– so-called standard employment- represents an important work reality. Within this reality, a sheer diversity of work typologies have proliferated, with the most well-known examples being fixed-term, part-time, and temporary agency work. In addition, other less typical forms of non-standard work have also been spreading in both developed and developing countries. Casual work arrangements constitute a prominent example in this latter scenario. These work arrangements have been frequently referred to through a wide range of terms, such as ‘on-call work’, ‘on-demand work’, ‘work with unpredictable work patterns’, ‘zero-hours work’, etc..
What is casual work?
From the outset, it should be made clear that casual work does not represent a unitary phenomenon, and as such, there is no universal definition on it . Definitional attempts have been, nonetheless, advanced by different institutions and scholars, in order to shed some light on the complexities surrounding casual work. These definitions seem to emphasize two main criteria for identifying casual work, namely the (very) short duration of the work, and the intermittent nature of the work. Against this background, casual work can be perceived as work of a very short duration, with some or no security of working hours, e.g. daily work, and work which is long-lasting but is characterized by an insecurity of working hours, e.g. zero-hours contracts. Zero-hours work arrangements can bring to extremes the insecurities already inherent in different forms of non-standard work, such as the insecurity of working hours, which goes hand in hand with that of jobs (work), and income. These insecurities can be, nevertheless, counteracted by means of regulatory answers, which can grant protections against them.
How have legislators responded to this phenomenon?
It was noted that different countries maintain a different regulatory approach to casual work. The difference was more striking between developing and developed countries. While casual work is widely present and regulated in many developing countries, developed countries experience an “underground casualization”, i.e. a lack of awareness and/ or a reluctance by legislators to govern this work typology. By having this in mind, it would be interesting to look into the legal landscape of some countries in relation to casual work. In the United Kingdom, for example, the spread of zero-hours work was publicly acknowledged many years ago. This did not prompt regulatory intervention; except for the prohibition against exclusivity clauses in these types of contracts. A different approach can be noted, nonetheless, in some other European countries. Netherlands, for instance, presents some good practices to regulate the phenomenon. In addition to stipulating a general legal presumption of an employment relationship, some specific safeguards on casual work have also been introduced, with the prominent example of the obligation for the employer to make an offer for fixed working hours after the worker has worked one year on-call. Furthermore, the Italian legislator has opted for a regulation of forms of casual work, by limiting them at the same time, e.g. by limiting the duration, or the allowed sectors. A peculiar feature of the Italian system is the provision of an availability indemnity, which is a monthly payment to compensate workers who promise to be available for calls of work. A more stringent regulatory pathway has been followed in Belgium, where intermittent work is allowed only in the tourism sector for up to two consecutive days, and with a maximum duration of days per year.
The ‘bad’ successor of casual work
Casual work has been among us for some centuries now, dating back to the daily work of dock workers in the late nineteenth century. Since then, it has proliferated in various sectors in both developing and developed countries. Nowadays, casual work arrangements can be spotted also under a “technological vest”, a phenomenon commonly referred to as platform work. This form of “internet-enabled casual work” is underpinned by the same (and even more) insecure working conditions as its “offline counterpart”, such as an insecurity of employment status, working hours, jobs, and income. These shared insecurity traits and the legal implication that the regulatory framework on casual work might have for the labour protection of platform workers, represent issues which will be further explored in an upcoming blog.
Accountancy , especially auditing and financial analysts, is a profession that is in high demand in South Africa. It holds a prominent position on the Department of Home Affairs’ critical skills list. However, one can’t ignore the growing decline that has plagued the profession with millennials and Gen Z’s opting for alternative career paths. In 2022, Gauteng education MEC Panyaza Lesufi tweeted that the interest in accounting taught in schools was dwindling as only 20,000 out of 140,000 matric learners in Gauteng were registered for the subject .
Accounting firms need to start considering how to boost the attractiveness of their businesses, and the profession at large, or risk dealing with a future talent gap like those being seen in U.S. and U.K. today. This begins with understanding the mismatch of millennial and Gen-Z aspirations and expectations and the reality that awaits them in the profession. Here are three starting points for making accountancy sexy to millennials and Gen Zs.
To foster retention, focus on mentorship
Often, when young professionals enter the work environment they struggle to convert their theoretical knowledge into practical use. This is when they actively seek mentors to provide them essential support to help to ‘fill in the blanks’ and share vital knowledge and wisdom from years of experience.
However, with the reality of work overload and long hours, there is often poor mentorship and guidance in the early stages, making the work environment monotonous and unfulfilling. Accountancy firms should prioritise early-stage career mentorship programmes that enculturate young entrants in a way that enables them to professionalise their knowledge, as they make the jump from graduate to professional.
Embrace their desire to create value
A large part of making the profession attractive to millennials and Gen Z is tapping into their desire to serve the public and contribute to tangible value creation. These are two of the most actively socially conscious generations today. Rote work that does not provide the opportunity to make an impact will leave younger employees feeling dissatisfied.
The profession is at a point where it is not only striving to regain public trust but also to reimagine a future for itself more firmly built on principles of ethics, societal consciousness, and transparency, as well as value creation on a business advisory level. Here, Gen Zs and millennials are well-aligned. To advance towards the aims of the profession, whilst maintaining a steady pipeline of talent, accountancy firms need to adjust their approach to advisory from mere bean-counting to providing strategic business advice that can create tangible value for clients. This will create opportunities for Gen Z to bring their talents to work, and collaborate particularly on project work across functions, disciplines and generations bringing multiple benefits that help generate new and innovative solutions and aid them in adding value to firms.
Let them claim their space in the digital world
It’s clear that the upcoming professionals are digital natives who are well-placed to take the reins in the second wave of 4IR, in which AI, data analytics and process automation are becoming commonplace. This means that the way in which the accountancy profession operates has to evolve in order to accommodate a constantly changing business and social environment. Millennials and Gen Zs are the professionals that can enable smoother adoption of increasingly used fintech tools. However, in order to do this, they need to be able to work at companies that are ready and able to make the digital leap.
According to the SAIPA Existing and Prospective Member Survey of 2021, new technologies are not used – or are only rarely used – by as many as 51% of the respondents. Barriers to adoption include budget constraints, customer resistance to change, limited knowledge about the benefits of new technologies, a lack of understanding of the importance of the digital transformation journey, and limited professional resources. Employers need to embrace the way younger professionals consistently question how things can be done quicker, better, and more efficiently. Alongside this, the crucial steps of training remain as essential as ever in building those capabilities across a business, to ensure no one is left behind – regardless of age.
And finally, keep an open mind
For any industry to remain relevant, it needs to court new entrants. Accountancy firms need to work with, rather than push against, the characteristics of the young professionals entering the profession. After all, they are the people who will be carrying the industry into the future. These tips have provided actionable first steps in firms not only attracting but retaining dynamic accountancy talent.
OECD countries just might be on the brink of an AI revolution. While adoption of AI is still relatively low in companies, rapid progress with generative AI (e.g. ChatGPT), falling costs, and the increasing availability of workers with AI skills mark a technological watershed for labour markets.
This is the assessment of the Organisation for Economic Co-Operation and Development (OECD) in its Employment Outlook 2023, released in July. As the organisation’s annual snapshot of labour markets across the world’s largest economies, it usually nails one focal point for the future. No surprise then that AI, which has been dominating the headlines since the start of the year, features as the main topic for 2023.
When considering all automation technologies, including AI, the OECD finds that 27% of jobs are in occupations at high-risk of automation. Initial conclusions from its new survey of AI’s impact on the manufacturing and finance sectors in seven countries highlight both opportunities and risks. On the positive side, the report says, AI can help reduce tedious and dangerous tasks, leading to greater satisfaction and safety. It also identifies a positive impact in terms of fairness in management and inclusion of disabled workers. Yet, 63% of workers in finance and 57% in manufacturing worry about job losses over the next 10 years due to AI.
Despite uncertainty about the evolution of AI in the short- to medium-term, the OECD recommends concrete policy actions to reap the benefits AI can bring to the workplace while addressing risks to workers’ fundamental rights and well-being. Certain jurisdictions, including the European Union, have already started regulating AI (e.g. EU Artificial Intelligence Act and data protection regulation) and the OECD also points to collective bargaining and social dialogue as important tools to support workers and companies in the AI transition.
As one example of social partners’ initiatives around AI, the OECD Employment Outlook 2023 quotes the code of conduct adopted by the World Employment Confederation in March 2023. Seeing the rapid deployment of AI in recruitment processes over the past few years, our sector deemed it essential to take an early stand in defining a set of standards that we could align on.
As a result, our Taskforce on Digitalisation led a cross-industry collaboration resulting in the adoption of a Code of Ethical Principles for the use of Artificial intelligence. It defines ten principles that members are required to apply in developing products, delivering services, and engaging partners when using AI.
AI offers strong potential to support both workers and employers in their labour market journeys. It plays a role in ensuring better and faster matching of supply with demand, improving the user experience, grounding labour markets in skills, and unlocking the data needed to do it. However, as with the introduction of any new technology or system, we need to ensure that the use of AI in the HR services sector is grounded in principles that place the needs of individuals and society at their heart.
Our Code recognises that AI is evolving, and so represents a set of 10 living principles which can be adapted over time. Unsurprisingly several principles focus on the need for human characteristics in AI systems used in the recruitment and employment industry: Human Centric Design – that provides beneficial outcomes for individuals and society; Human in Command – in order that they are designed to augment human capabilities with clear processes in place to ensure that they always remain under human direction and control; and Building Human Capacity – enhancing workers and managing fair transitions through the implementation of life-long learning, skills development, and training.
Other principles focus on the need for openness and responsibility. Transparency, Explainability, and Traceability – to ensure that those using AI systems are transparent about their use of technology and provide workers and employees with information about their interactions with AI systems, explaining how these systems arrive at their decisions; and Accountability to ensure that those deploying AI systems take responsibility for their use at all times.
The 10 principles also address protection of people and systems: Privacy requires that AI systems used by the recruitment and employment sector comply with the application of general privacy principles and protect individuals against any adverse effects of the use of personal information in AI; Safety & Security ensure that systems are technically robust and reliable, with monitoring and tracking processes in place to measure performance and retrain or modernise as necessary. Naturally, ethical governance also features as a principle, with WEC encouraging frameworks to ensure the ethical development and use of AI – including the involvement of relevant stakeholders such as government, civil society, and academia in the decision-making process.
Two further principles focus on broader societal objectives: Fairness and Inclusivity by design seeksto ensure that the AI systems used by the sector treat people fairly and respect the principles of non-discrimination, diversity, and inclusiveness. It requires that appropriate risk assessment and mitigation systems be implemented throughout the AI system lifecycle. Environmental and societal well-being aims to ensure that AI systems are designed and used in a way that considers the environmental and societal impacts of their use.
At the core of our principles lies the need to keep a human-centric approach to artificial intelligence and lay the foundations for building better labour markets. The OECD Employment Outlook 2023 rightfully flags, trustworthy use of AI is key. As organisations move ahead and embrace AI across their business Governments need to ensure that it continues to serve to support inclusive labour markets as opposed to hindering them, thereby bringing opportunities for all.
While artificial intelligence (AI) is by no means new technology, its parameters are constantly shifting thanks to the introduction of new AI tools, thereby revolutionising what AI makes possible. It’s for this reason that headlines across the media have recently been awash with mention of ChatGPT and all its ramifications, including its impact on accountancy professionals.
Much like most other industries, professionals in the accountancy world have questioned how AI tools like ChatGPT will impact their roles, specifically whether the technology is a threat to their jobs. It is important to acknowledge that AI, like any other advancement in technology, is simply a tool that can and should be used by Professional Accountants (SA) to improve the quality, efficiency, and effectiveness of their services.
While AI does have the ability to take on some aspects of an accountancy professional’s role, there’s no reason to fear the worst just yet. AI and technology in general are not going to take over the work of Professional Accountants (SA) in a hurry. It’s important that we see them as enablers to providing clients and the industry at large with more value-added services.
Shifting accountancy beyond the numbers
Burying one’s head in the sand when it comes to AI is simply not an option. Instead, Professional Accountants (SA) should aim to embrace the technology for all its benefits, using it as a tool to move away from data capturing and the stereotypical notions of ‘number crunching’ typically associated with the profession, and into the analysis of data in ways that only human Professional Accountants (SA) are capable of.
This is the opinion of SAIPA as a Professional Accountancy Organisation representing qualified Professional Accountants (SA) in South Africa, having expressed its stance on AI as an enabler of innovation in the profession, and a gateway for Professional Accountants (SA) to enhance their skills in areas relevant to the fourth industrial revolution (4IR).
SAIPA endorses the use of ChatGPT and other AI chatbots as a means for Professional Accountants (SA) in research and data gathering to support management with decision making and problem solving. SAIPA is in the process of revising its education and assessment models to this effect. However, the focus of learning will be on interrogating the information gathered to support the development of critical thinking, professional scepticism, problem-solving, and professional judgment.
Looking at AI from a more positive perspective in this way reveals a number of advantages for the accountancy professional with a future-focused mindset – that is, one who hopes to remain relevant by keeping their skills, experience and services in adherence to the ever-changing demands of modern businesses.
For instance, AI can assist in enforcing corporate policy by identifying non-compliance issues and errors in financial data. It can also streamline the data entry and analysis process by recognising and categorising financial transactions from receipt images, using this to provide accurate reports that managers can peruse and analyse far more efficiently. In both instances, technology frees up the Professional Accountant’s (SA) time to focus more on information analysis.
Where fraud and corruption are a common and unfortunate reality in South Africa, AI can act as an independent auditing tool to assess transactions and reports, predict patterns and detect a wide variety of irregularities in financial data.
AI can also be used in budget forecasting to predict a company’s future financial performance based on historical and current financial data, not to mention facilitate tax preparation by extracting relevant information from financial documents to be used in the creation of tax returns.
From a talent acquisition and retention point of view, AI chatbots can assist in the areas of HR recruitment and employee experience, streamlining and optimising HR processes while offering candidates personalised insights into the skills they need to focus on developing as well as possible growth paths in the company and in their careers.
AI is not the enemy; it provides us with data, but it’s certainly no substitute or replacement for human interpretation and expertise. AI is a handy and increasingly necessary companion for Professional Accountants (SA) navigating accountancy and business in the digital age. Embracing technology in this way has a number of benefits for the individual and the industry at large, from streamlining processes to enabling Professional Accountants (SA) to take more of a data analysis and advisory role to their clients.
Tax season doesn’t need to be a disaster. Several best practices have been put in place to help you get file your taxes seamlessly as possible.
Chi Chi Gule chats with Mahomed Kamdar, Tax Specialist at the South African Institute of Professional Accountants (SAIPA), as he outlines the key steps one can incorporate to ensure deadlines are met, compliance is achieved, and key resources at your disposal to consider.
What are the do’s of individual filing to ensure a smooth tax filing experience?
Firstly, determine whether you, the taxpayer, earns income from sources other than a salary. Once the taxpayer earns income from sources other than being a salaried employee during the year of assessment, then the person is a provisional taxpayer. If the taxpayer was a provisional taxpayer in a prior tax-year, there is no guarantee that the same taxpayer will forever be a provisional taxpayer or vice versa. The taxpayer could have changed the nature of their transactions recently thereby terminating their provisional tax status. If the status of the taxpayer has changed then the timeframe for the submission of tax return also changes. This could result in late submission of tax returns and consequently, administrative non-compliance penalties can be invoked, if the timeframe for the submission of tax returns adhered to is for provisional taxpayers although the provisional tax status of the taxpayer has ended.
Secondly, you must have all supporting documents which provide evidence for the information submitted in the tax return before submitting a tax return electronically. In this way, you will not `panic’ when audited by SARS because all documentary evidence is already available in a format which can be easily forwarded to SARS. As far as possible, avoid searching for documentary evidence on the eve of a SARS audit. Doing this would remove stress for both the taxpayer and tax practitioner.
Finally, confirm that your bank details, IRP5 statements, cell numbers and email addresses are correct. If you find that your tax refunds have been transferred to your `old’ accounts, SARS will not be responsible for the incorrect destination of tax refund. SARS could also impose administrative non-compliance penalties if the taxpayer fails to disclose their correct personal contactable details.
What are the don’ts of individual filing to ensure a smooth tax filing experience?
Don’t hide non-salaried income from SARS even if you are auto assessed. Although the income could be exempt or falls below the threshold, it must be included in the gross income of the individual. It is possible that a taxpayer is auto assessed and SARS is not aware other income stream. Under these circumstances, the taxpayer should amend the assessment and not `accept ‘the results of the auto assessment. The result of auto assessment can be reversed in the future should SARS uncover the additional income stream. Under these circumstances, SARS could impose the vicious understatement penalty.
Definitely do not delay on your submission of tax returns because of inconveniences like load shedding, unless there is a valid reason which SARS will accept. Retain documents and other forms of evidence to support the reason for late submission. SARS holds the view that taxpayers have an advanced knowledge of when load shedding will occur, and taxpayers should work around these load shedding schedules to submit tax returns.
Thirdly, taxpayers should not hide their capital gains after selling their fixed immovable primary residence or their holiday homes. This is especially important for the completion of provisional tax.
What are some of the new and improved ways SARS is tightening up on compliance?
SARS has embarked on a digital transformation journey, introducing new digital initiatives and innovations to support tax compliance. SARS has moved away from a solo approach to tax administration, that is, placing reliance on the information provided by taxpayers with accompanying supporting documents. Tax has become more integrated with the provisions of other services and is no longer viewed as a stand-alone activity. In other words, tax collection has become less reliant on voluntary compliance. SARS is using technology tools to perform 3rd party verification, such as medical aid contribution, bank interest, property, and vehicle registration. The chance of being caught out increases exponentially.
How is improved technology, the use of data, artificial intelligence and algorithms enabling SARS to boost compliance with tax obligations?
Artificial intelligence has enabled SARS to significantly expand its scope of detecting tax fraud, beyond data obtained through declarations. SARS implemented several machine learning models that leverage multiple asset and income stream data sources to detect non-, as well as under-declaration of tax liability. In the case of tax, AI is used to determine trends, taxpayer behaviour and other information that impact tax returns or the calculation of taxable system. In the era of smart machines, the advancement in technology has improved the ability of SARS to detect irregular or suspicious trends in tax returns.
Technology tools will also improve the efficiency and speed with which SARS will be able to assess taxpayers. Auto assessment is a permanent feature of our tax system; it will improve in future through the development of AI-powered tools and will increase the mode of revenue collection. Linked to this is the creation of a robust connective tax network, whereby SARS can access information like personal details from 3rd parties. This information serves as part of a “Big Data” network.
In the future, sales, and purchases by companies and sole proprietors could be recorded in a centralised information platform for authorised users to extract and utilise. Given the state of technological development, SARS could well `auto’ assess VAT 201 on behalf of vendors. This will take indirect taxes to a new height, where the assessments can be done in real time based on the recording of the transaction in an inter-connected digital platform and environment. This is possible for retail outlets using cash registers which could be linked to a central database from which SARS obtains information.
Additionally, SARS is not only upgrading its internal processes. It is now capable of seamlessly sharing data with authorities around the world to discover foreign caches of undeclared income. It is important to note that the sharing of tax information locally or globally does not violate the provisions of the Protection of Personal Information (POPI) Act 4 of 2013. The provisions of POPI simply do not apply to the collection of tax revenues. Taxpayers are legally obliged to disclose information required to complete a tax return.
How do auto-assessments work? What are the next steps to take if you are unhappy with your auto assessment?
Auto assessments begin with data collection. SARS receives data from employers, medical schemes, banks, retirement annuity funds, and other institutions. Legislation requires service providers to provide data which SARS can access for verification. This data is used to assess whether there is a refund due to the taxpayer or whether an amount must be paid to SARS. If SARS is satisfied that the data and tax calculation is correct, then SARS will issue an assessment to the individual taxpayer via eFiling or the SARS MobiApp. At the same time, SARS will also send the individual taxpayer a message via the taxpayer’s preferred channel of communication (like SMS or email) to let the taxpayer know that assessment is ready for the taxpayer or their tax practitioner to view. From Friday 30 June 2023, SARS will communicate directly with selected taxpayers via SMS notifying taxpayers of their auto-assessments.
In 2023, taxpayers who are eligible for auto assessment will also receive a letter from SARS confirming that they fall within the auto assessment scope during the 2023 tax filing system. This is a new development when compared with the 2022 tax filing system. Taxpayers will know in advance that they are candidates for auto assessment. The issuing of letters by SARS provides taxpayers with an early opportunity to examine if they were incorrectly subjected to auto assessment.
SARS will issue auto assessment letters from 1 July 2023, even though the 2023 filing season will only begin on 7 July. The early release of auto assessment letters provides taxpayers with two key benefits, namely: increased time to review the auto assessment and determine whether they are correctly subjected to auto assessment, and secondly enhanced accuracy, as a thorough examination of the assessment outcome ensures that any potential errors or discrepancies can be identified and addressed in a timely manner.
If a taxpayer is not pleased with the outcome of their auto assessment, SARS will be allowing individual taxpayers until 23 October 2023 to file an amended return which is also the deadline to submit tax returns by non-provisional taxpayers who have not been auto assessed. If a taxpayer agrees with their auto assessment, and a refund is due, then there is nothing more for them to do – simply wait for the refund, which you can expect within 72 hours. If you owe SARS, then you must make a payment either via eFiling, SARS MobiApp or via EFT on or before the payment due date (30 days after statement date).
Discover the potential of artificial intelligence with our comprehensive cheat sheet. Learn more about the concepts, platforms and applications of AI.
Artificial intelligence comes in many forms, from simple tools that respond to customers via a chat to complex machine learning algorithms that predict the trajectory of an entire organization. Despite years of overpromising, AI doesn’t comprise sentient machines that reason like humans. Rather, AI encompasses more narrowly focused pattern matching at scale to complement human reasoning.
In order to help business leaders understand what AI capabilities are, how to use artificial intelligence and where to begin an AI journey, it’s essential to first dispel the myths surrounding this huge leap in AI technology.
AI is largely a pattern-recognition tool that can run at a scale that’s dramatically beyond any human, yet never quite replaces humans. Even at its best, AI delivers acceptable, though not perfect results, giving people the ability to step in, observe the data and reason from there.
Note that while we use AI throughout this cheat sheet, most enterprises actually engage with a subset of AI called machine learning or deep learning. We’ll use AI here as a shorthand that includes machine learning and deep learning.
The truth is that current AI technology is limited, but it’s still incredibly powerful. However complicated its processes may seem in practice, at the core of AI-driven applications is the simple ability to identify patterns and make inferences based on those patterns.
AI isn’t truly intelligent, and it’s often as biased as the data we choose to feed into our ML models. That doesn’t mean AI isn’t useful for businesses and consumers trying to solve real-world problems, it means that we’re nowhere close to machines that can actually make independent decisions or arrive at conclusions without being given the proper data first. It’s also true that AI can tend to confirm our biases, rather than eliminate them.
How does artificial intelligence work?
AI is a complex system designed to model human behavior and intelligence. It combines large data with intelligent algorithms to analyze, understand, and make decisions or predictions about future states. To make accurate predictions, AI systems require large amounts of data to learn from; this data is gathered from various sources, processed, analyzed and organized in a suitable format for the AI algorithms.
AI algorithms are the core of AI systems and are designed to analyze and interpret data, identify patterns, and make predictions or decisions based on the input. By continuously collecting new data and retraining the models, AI systems can adapt to changing conditions and improve their performance.
The core process of how AI works involves the following subdomains:
Machine learning: A branch of AI that focuses on the development of algorithms and statistical models that allow computer systems to learn and improve from data without being explicitly programmed.
Deep learning: A subfield of machine learning that mimics the workings of the human brain’s neural networks, using multiple layers of artificial neural networks to learn and understand complex patterns and features in data.
Neural networks: A computational model, inspired by the structure and function of the human brain, that can process and analyze large amounts of data to recognize patterns, make predictions or classify information.
Natural language processing: A branch of AI that focuses on the interaction between computers and human language, enabling machines to understand, interpret and generate human language.
Computer vision: A branch of AI that enables machines to interpret and understand visual information from images or videos.
Cognitive computing: A model that aims to create AI systems that can simulate human-like intelligence and interact with humans in a more natural and intuitive way.
What can artificial intelligence do?
Artificial intelligence is essentially pattern matching at scale. With its pattern recognition capabilities, modern AI can perform image recognition, understand the natural language and writing patterns of humans, make connections between different types of data, identify abnormalities in patterns, strategize, predict and more.
While humans are unable to as easily comb through the amount of data that machines can to uncover patterns, machines struggle when presented with an outlier that might be easy for a human to spot but contradicts the training data. Therefore, the best AI applications are highly focused and combine human reasoning with the brute power of ML.
Since the onset of the COVID-19 pandemic in 2020, AI and ML have seen a massive market growth. The global pandemic also shifted AI priorities and applications: Instead of solely focusing on financial analysis and consumer insight, post-pandemic AI projects have trended toward customer experience and cost optimization.
AI bots can perform many basic customer service tasks, freeing employees up to only address cases that need human intervention. AI like this has been particularly widespread since the start of the pandemic, when workers forced out of call centers put stress on customer service.
What are the business applications of AI?
In the business world, there are plenty of AI applications, but perhaps none is gaining traction as much as business and predictive analytics and its end goal: prescriptive analytics.
Business analytics is a complicated set of processes that aim to model the present state of a business, predict where it will go if kept on its current trajectory and model potential futures with a given set of changes. Predicting the future with an established model of the past can be easy enough, but prescriptive analysis, which aims to find the best possible outcome by tweaking an organization’s current course, can be downright impossible without AI help.
Analytics may be the rising star of business AI, but it’s hardly the only application of artificial intelligence in the commercial and industrial worlds. Other AI use cases for businesses include the following:
Recruiting and employment: AI can streamline recruiting by filtering through larger numbers of candidates more quickly than a human and by noticing qualified people who may be overlooked.
Fraud detection: AI is great at picking up on subtle differences and irregular behavior, such as subtle indicators of financial fraud that humans may miss.
Cybersecurity:AI is great at detecting indicators of hacking and other cybersecurity issues.
Data management: Using AI, you can categorize raw data and find relationships between items that were previously unknown.
Customer relations: Modern AI-powered chatbots are incredibly good at carrying on conversations thanks to natural language processing, making them a great first line of customer service.
Healthcare: Not only are some AI applications able to detect cancer and other health concerns before doctors, they can also provide feedback on patient care based on long-term records and trends.
Predicting market trends: Much like prescriptive analysis in the business analytics world, AI systems can be trained to predict trends in larger markets, which can lead to businesses getting a jump on emerging trends.
Reducing energy use: AI can streamline energy use in buildings and even across cities as well as make better predictions for construction planning, oil and gas drilling, and other energy-centric projects.
Marketing: AI systems can be trained to increase the value of marketing both toward individuals and larger markets, helping organizations save money and get better marketing results.
What are the different types of AI?
Narrow AI
Also known as weak AI, narrow AI helps you perform specific functions. It’s focused on a single domain and operates within predefined limits. Narrow AI cannot do anything more than what they are programmed to do — they have a very limited or narrow range of competencies. Examples include voice assistants like Siri or Alexa. These lack general intelligence and cannot perform tasks outside their designated domain.
General AI
General AI, also known as strong AI or artificial general intelligence, refers to AI systems that possess human-level intelligence and can understand, learn and perform any intellectual task that a human being can do. They can adapt to various scenarios and solve problems creatively. While general AI remains a long-term objective, current advancements primarily focus on developing narrow AI systems that excel in specific areas, such as image recognition or natural language processing.
Superintelligent AI
This type of AI surpasses human intelligence in nearly all aspects. It not only outperforms humans in cognitive tasks but also possesses the ability to improve itself, leading to an exponential increase in intelligence. While superintelligent AI remains largely theoretical at present, it’s a topic of interest and concern within the field of AI.
Reactive machines
Reactive AI systems automatically respond to a limited set or combination of inputs and operate based on the current input without any memory or past experiences. In fact, reactive AI systems don’t have the ability to form memories or learn from previous interactions. They simply react to the current situation or stimulus. Examples include chess-playing AI systems or recommendation algorithms.
Limited memory
AI systems with limited memory can store and retrieve information from previous experiences to make better decisions. They have the ability to learn from past data and use it to improve their future actions. Self-driving cars that use historical data to make driving decisions are an example of limited memory AI.
Theory of mind
This type of AI is still largely theoretical. Theory of mind AI will have the ability to understand and model the mental states, beliefs, and intentions of other agents. They’ll be able to attribute thoughts, emotions, and intentions to other entities and predict their behavior based on this understanding.
Self-aware
While still theoretical and not fully realized, this type of AI would possess human-like awareness and understanding of its own existence. Self-aware AI systems will have a sense of their own existence, consciousness and internal state. They possess self-reflective abilities and are aware of their own thoughts, actions and impact on their environment. True self-aware AI is a concept that remains largely speculative and is currently beyond the capabilities of existing technology.
Generative AI
Generative AI systems are capable of creating content, such as images, videos, music or text, that is nearly indistinguishable from human-generated content. They can autonomously generate new outputs based on their learned patterns and styles.
Generative adversarial networks are an example of generative AI, where one network generates content, and another network evaluates and provides feedback to improve the quality of the generated output.
DeepArt.io: This tool uses neural networks to transform photos into artistic styles from famous artists.
Runway: This platform offers a range of generative AI tools for creating images and videos.
DeepDream: DeepDream is a tool developed by Google that uses generative AI to modify images. It enhances patterns and structures in an image to create dream-like visuals.
OpenAI’s ChatGPT: Generative pretrained transformer is a language model developed by OpenAI to generate human-like text based on a given prompt. The latest model GPT-4 was trained on Microsoft Azure AI supercomputers and is available on ChatGPT Plus.
What AI platforms are available?
When adopting an AI strategy, it’s important to know what software is available for business-focused AI. There are a wide variety of platforms available from the usual cloud computing suspects like Google, AWS, Microsoft and IBM, and choosing the right one can mean the difference between success and failure.
AWS Machine Learning
AWS Machine Learning offers a wide variety of services that run in the AWS cloud. AI services, prebuilt frameworks, analytics tools and more are all available, with many designed to take the legwork out of getting started and others like SageMaker for Business Analysts designed to enable corporations to get AI insight without writing code. AWS offers prebuilt AI algorithms, one-click ML training and training tools for developers getting started in or expanding their knowledge of AI development.
Google Cloud
Google Cloud offers similar AI solutions to AWS, as well as having several prebuilt total AI solutions that organizations can ideally plug into their organizations with minimal effort. Google also distinguishes itself by innovating some of the industry standards for AI like TensorFlow, an open-source ML library.
SEE: Discover Google’s latest generative AI platform Google Bard
Microsoft AI
Microsoft’s AI platform comes with pre-generated services, ready-to-deploy cloud computing infrastructure and a variety of additional AI tools that can be plugged into existing models. Its AI Lab also offers a wide range of AI apps that developers can tinker with and learn from what others have done. Microsoft also offers an AI school with educational tracks specifically for business applications.
Watson
Watson is IBM’s version of cloud-hosted ML and business AI, but it goes a bit farther with more AI options. IBM offers on-site servers custom built for AI tasks for businesses that don’t want to rely on cloud hosting, and it also has IBM AI OpenScale, an AI platform that can be integrated into other cloud hosting services, which could help to avoid vendor lock-in. In 2021, IBM Watson suffered a media backlash after years of overpromising on what its AI could deliver in healthcare, but many enterprises still turn to it for narrower tasks.
What AI skills will businesses need to invest in?
Perhaps the most critical skill needed to use AI is knowing when to skip AI altogether. The reality of AI is that many problems could be solved by applying simple regression analysis or if/then statements. Most AI, in other words, isn’t AI at all: It’s only basic math and common sense.
For more complicated, AI-oriented tasks, the associated data science breaks down into two categories: that which is intended for human consumption and that which is intended for machine consumption.
In the latter case, AI involves complex digital models that apply ML models and AI algorithms to large amounts of data. These systems then act autonomously to generate a particular ad or customer experience or make real-time stock trades. Hence, machine-oriented AI professions require “exceptionally strong mathematical, statistical and computational fluency to build models that can quickly make good predictions,” as former Google and Foursquare data scientist Michael Li has noted.
By contrast, the skills needed for more human-oriented data science and AI skew toward storytelling. Given that no data is unbiased, the role of human intelligence is to help the data tell clear stories. Such AI storytellers use data visualization to facilitate exploration and insights into that data.
For many in AI, the most sophisticated math they’ll do is power analyses and significance tests. They might write SQL queries to get data, do basic math on that data, graph results and then explain the results. Not gee whiz data science, but it’s incredibly helpful for breaking down complex data into actionable insights, to use the data science lingo.
With all that in mind, it’s still true that skills needed for an AI project differ based on business needs and the platform being used, though most of the biggest platforms support most, if not all, of the most commonly used AI programming languages and skills needed.
Many business AI platforms offer training courses in the specifics of running their architecture and the programming languages needed to develop more AI tools. Businesses that are serious about AI should plan to either hire new employees or give existing ones the time and resources necessary to train in the skills needed to make AI projects succeed.
How can businesses start using AI?
Getting started with business AI isn’t as easy as simply spending money on an AI platform provider and spinning up some prebuilt models and algorithms. There’s a lot that goes into successfully adding AI to an organization.
At the heart of it, all is good project planning. Adding artificial intelligence to a business, no matter how it will be used, is like any business transformation initiative. Here’s an outline of just one way to approach getting started with business AI.
Determine your AI objective
To begin, figure out how AI can be used in your organization and to what end. By focusing on a narrower implementation with a specific goal, you can better allocate resources.
Identify what needs to happen to get there
Once you know where you want to be, you can figure out where you are and how to make the journey. This could include starting to sort existing data, gathering new data, hiring talent and other pre-project steps.
Build a team
With an end goal in sight and a plan to get there, it’s time to assemble the best team to make it happen. This can include current employees, but don’t be afraid to go outside the organization to find the most qualified people. Be sure to allow existing staff to train so they have the opportunity to contribute to the project.
Choose an AI platform
Some AI platforms may be better suited to particular projects, but by and large, they all offer similar products in order to compete with each other. Let your team give recommendations on which AI platform to choose — they’re the experts who will be in the trenches.
Begin implementation
With a goal, team and platform, you’re ready to start working in earnest. This won’t be quick: AI machines need to be trained, testing on subsets of data has to be performed and lots of tweaks will need to be made before a business AI is ready to hit the real world. In fact, you should expect that the vast majority of your time won’t be spent in crafting sexy algorithms, but rather in data preparation. ... Original post > TechRepublic by Aminu Abdullahi
Social media has been flooded with chatter about the chatbot phenomenon ChatGPT which seems destined to be able to, if not far better do, what humans can! So, what does this mean for employees? Can an employee be replaced by a bot like ChatGPT? In this article, we take a closer look at what this could mean for employees in the not-so-distant future.
ChatGPT is an artificial intelligence chatbot which can not only assimilate vast quantities of data and provide startlingly accurate information and insights but can also assist with a range of tasks such as creating graphics, answering questions and composing music, tasks to date perceived to fall squarely within the capabilities of humans only.
However, with a bot like ChatGPT passing the final exam for the MBA programme in research at the University of Pennsylvania’s Wharton School of Business, questions start abounding about whether the ‘reserved for humans only’ abilities are still so reserved, and if no longer, what this means for humankind.
ChatGPT can perform and ‘automate’ skills possessed by paid workers owing to its advanced knowledge and ability to produce human-like answers. Have a query on your mind? Simply insert the query and ChatGPT has you covered, in many cases more comprehensively than your average person would or could do.
As with any new technology, there are concerns, especially regarding the accuracy of the answers it provides and intensive research is being conducted into the model. However, without a doubt, the impact and potential of ChatGPT have been felt and businesses are already planning to integrate the functionality of a bot like ChatGPT into their workplace. ‘And why not?’ you may ask. It’s highly accurate, works at the speed of light, and provides amazingly accurate responses to complex tasks.
On the flip side, it also means that many of the jobs which an AI bot may replace, and currently performed by humans, will be rendered obsolete by this new technology. Think of financial, media, legal and other industries heavily reliant on data and its assimilation. An AI bot could do the data crunching of hundreds of lawyers or produce news content to replace a regiment of journalists.
Such a reality, which seems likely given the apparent capabilities of ChatGPT, will potentially render redundant certain categories of employees, now to be performed by AI. But what will happen to employees in positions now rendered redundant? Can the employer just fire them?
So, “no” the employer cannot just fire them, but “yes” these employees could be retrenched and in such a manner lose their jobs. In South Africa, this would mean that the employer would have to follow the retrenchment procedures as set out in the Labour Relations Act. Nevertheless, such employees may be facing unemployment because of AI.
According to our labour laws, retrenchment processes can be undertaken when an employer, due to the economic, structural or other needs of the business, contemplates retrenching employees. Such needs can include the introduction of new technologies capable of performing tasks which would otherwise be performed by an ordinary human employee.
To give credence to this threat, various tech companies around the world such as Amazon, Microsoft and Google have retrenched employees due to the developments in the technology industry. Microsoft is currently in the process of retrenching thousands of its employees as it invests billions in AI.
As much as AI is unlikely to be an immediate threat to South African jobs, note must be taken of these developments to ensure that both employer and employee alike are prepared for a future that heralds an increasing prevalence of AI in all facets of our lives. It’s time to reimagine and rethink the way we work, so that human persons and AI can work together towards efficient and high-quality productivity.
This article is a general information sheet and should not be used or relied on as legal or other professional advice. No liability can be accepted for any errors or omissions nor for any loss or damage arising from reliance upon any information herein. Always contact your adviser for specific and detailed advice. Errors and omissions excepted (E&OE) ... Original post > Human Alliance
