{"id":148378,"date":"2025-09-01T06:34:50","date_gmt":"2025-09-01T06:34:50","guid":{"rendered":"https:\/\/news.sap.com\/africa\/?p=148378"},"modified":"2025-09-01T06:34:51","modified_gmt":"2025-09-01T06:34:51","slug":"preparing-for-the-workplace-impact-of-artificial-general-intelligence","status":"publish","type":"post","link":"https:\/\/news.sap.com\/africa\/2025\/09\/preparing-for-the-workplace-impact-of-artificial-general-intelligence\/","title":{"rendered":"Preparing for the Workplace Impact of Artificial General Intelligence"},"content":{"rendered":"
\n

\"\"What happens when machines and algorithms can complete knowledge work faster and more effective than even the most high-performing teams?<\/p>\n

Thanks to the accelerating power, speed and accuracy of artificial intelligence (AI) over the past few years, the arrival of artificial general intelligence (AGI) is no longer a matter of what-if, but of when.<\/p>\n

Artificial general intelligence refers to machine intelligence that can perform any intellectual task a human can.<\/p>\n<\/div>\n

\n

Today\u2019s generative AI solutions, such as DALL-E and ChatGPT, excel in narrow, specialised domains, for example image creation or text editing. In contrast, artificial general intelligence would rival or exceed human cognitive abilities across a wide range of tasks, including creativity, planning, problem-solving and reasoning.<\/p>\n

AGI will have a seismic impact on work and employment, completely transforming how companies operate and what types of skills employees need to remain competitive in an increasingly uncertain job market.<\/p>\n

And time is running out for employers and knowledge workers to plan for this impact:\u00a0some researchers suggest<\/a>\u00a0AGI will arrive around 2041, although\u00a0more recent predictions<\/a>\u00a0estimate it could arrive as early as 2026.<\/p>\n<\/div>\n

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Profound jobs impact expected<\/b><\/h2>\n<\/div>\n
\n

The impact of AGI on knowledge work is predicted to be significant.\u00a0Up to two-thirds of jobs in the US and Europe<\/a>\u00a0are vulnerable to some form of automation.<\/p>\n

Many professions that have traditionally be high paying, such as coding, business analysis, and creative design, are squarely in the sights of AI. In fact, any job where \u2018knowing the answer\u2019 was the key to performance will be transformed by AGI.<\/p>\n

Young professionals are likely to experience the greatest impact from AGI. Many entry-level jobs involve routine office work, with junior positions often designed to provide young workers with vital experience into how companies operate and what a specific career entails.<\/p>\n<\/div>\n

\n

Organisations will have to transform the nature of entry-level jobs to ensure that younger employees have opportunities to contribute meaningfully to company success.<\/p>\n

Skills programs that prioritise how young workers can leverage AI and AGI to perform with greater efficiency could safeguard junior positions and ensure entry-level employees remain valuable contributors to broader organisational goals.<\/p>\n

Experienced workers can also benefit from AI\/AGI training:\u00a0a report by the World Economic Forum<\/a>\u00a0revealed that 40% of employers expect to reduce their workforce where AI can automate tasks, highlighting the need for workers to rapidly upskill in the face of AI-led workplace transformation.<\/p>\n<\/div>\n

\n
Tidal wave of career change incoming<\/b><\/div>\n<\/div>\n
\n

To prepare for the imminent impact of AGI, knowledge workers should make continuous upskilling a non-negotiable, no matter their level of seniority or experience.<\/p>\n

Research indicates that the average half-life of technical and soft skills\u00a0has dropped from around 30 year to only six<\/a>.<\/p>\n<\/div>\n

\n

Embracing learning agility could become an anchor of future career security, with AI-powered personalised learning expected to play a major role as traditional degrees continue to lose value.\u00a0Workers should also lean into the qualities that are uniquely human.<\/p>\n

While AGI means answers will be easy to come by, understanding the right question to ask – through interpreting and contextualising problems – will be a foundational skill in knowledge work.<\/p>\n

This increases the importance of skills such as problem framing, critical thinking, and storytelling-based communication.<\/p>\n<\/div>\n

\n
Other human-first skills such as emotional intelligence, creativity and the ability to ask meaningful questions will also be difficult for AGI to replace and should be prioritised as part of lifelong learning efforts.<\/div>\n<\/div>\n
\n

Preparing the enterprise for AGI<\/b><\/h3>\n

Companies need to take steps too. Investing in regular upskilling and reskilling initiatives will help modernise their workforce and ensure a steady supply of relevant skills.<\/p>\n

Encouragingly,\u00a0recent research conducted by SAP<\/a>\u00a0revealed that 48% of African organisations consider the upskilling of their employees a top skills-related challenge this year, with 38% saying the same of reskilling.<\/p>\n<\/div>\n

\n

This figure should increase or companies may soon realise they cannot keep pace with changing skills-related demands.<\/p>\n

Rethinking hiring strategies could also benefit organisations. Instead of a reliance on degree-based hiring, companies could embrace skills-based assessments where qualities such as adaptability, creative problem-solving and collaboration are prized.<\/p>\n

Finally, companies need to develop robust internal policies to manage AGI integration, ethics and reskilling, rewiring their organisational DNA by embedding lifelong learning in every role and department.<\/p>\n<\/div>\n

\n
Preparing for AGI requires that companies and professionals look beyond traditional education and career models.<\/div>\n<\/div>\n
\n

The goal is to adapt at the pace of technology, and to nurture the deeply human skills that technology cannot emulate or replace.<\/p>\n

Nazia Pillay, Managing Director for Southern Africa at SAP.<\/i><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

What happens when machines and algorithms can complete knowledge work faster and more effective than even the most high-performing teams? 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