How AI is reshaping business and empowering people

The artificial intelligence (AI) revolution eclipses even the seismic impact of the Internet boom in the 1990s, propelled by the unprecedented speed of innovation and exponential growth in data. It marks a fundamental shift in human capability that cannot be stopped.

AI is rapidly transforming every industry and sphere of work, with more than three-quarters of respondents in The State of AI survey conducted by McKinsey & Co. stating that their organisations currently use AI in at least one business function.

While this rapid adoption rate has many people worried about their role and relevance in the workplace, the overriding theme of the unfolding AI revolution is that the technology is augmenting—rather than replacing—human workers, enhancing productivity, driving operational efficiencies, and unlocking organisational value.

McKinsey & Co. terms it superagency – AI’s ability to “amplify human agency and unlock new levels of creativity and productivity in the workplace.”

Microsoft CEO Satya Nadella shares a similar sentiment, stating that AI has the potential to solve complex global problems, transform knowledge work, and create new opportunities. However, the biggest challenge we face, according to Nadella, is changing how people work with AI-driven workflows. 

AI holds the potential to unlock human capital in an organisation by giving people more time to focus on what they do best, or on higher-value work. For example, agentic AI co-pilots can handle any repetitive or volume-based tasks for us. In a real-world application achieved at one of our customers, a team of chartered accountants reduced the time needed to compile a 69-page report with graphs and insights from a week to just four minutes by using an agentic AI co-pilot.

Microsoft also recently released over 11 000 models in Azure Studio, where staff members can use these AI models to enhance their state of work, linking different systems, such as Outlook email to schedule follow-ups in their calendars, check the external CRM database and update the details automatically.

Newer agents are also emerging that perform specific roles, such as sales agents, human resource agents, financial bots, development bots and others. These multi-agents will drive a new wave of intelligent business automation.

However, these capabilities only become possible if AI solutions are correctly implemented and accompanied by active reskilling and upskilling. Success in the AI age is predicated on the ability to leverage organisational data, with the right training to exploit the full potential of this transformative technology.

AI works best when data leads the way. Organisations that become data-powered can better prioritise where to apply AI in the business — whether that is intelligent automation, predictive customer experience (CX), or decision intelligence.

Multi-modal AI must combine data from internal and external sources to deliver the strategic outcomes a business desires, whether that’s increased sales, better customer service, or operational efficiency. Data growth is also exploding due to advances in AI, machine learning (ML), real-time analytics, multi-modal data models, hybrid clouds and edge computing. 

For this reason, 40% of any AI project should focus on strategic planning and data structuring to align with the business objective. Historically, this phase only accounted for 20% of technology implementations. 

The focus – up to 40% - in legacy implementations concentrated on the build phase. However, that figure is now 20% as AI also assists developers in writing the necessary code.

The remaining 40% of an AI project must focus on adoption and drive inclusive usage to deliver a return on investment. As such, adoption and change management (ACM) has become a critical element in any AI project, and is where projects typically fail to deliver value.

ACM requires training and coaching that empowers teams to use the new AI tools confidently and effectively.

Given these dynamics, we foresee that the next five years will focus on the integration of AI co-pilot agents in the workplace.

As more data centre capacity comes online, with huge capital expenditure from major players including Microsoft, Amazon Web Services, and key infrastructure providers, the next phase in AI adoption will focus on the orchestration of data collaboration between structured and unstructured data.

The term BYOM (bring/build your own model) will also become more prevalent, as will hybrid cloud models that support computing at the edge, especially in regions like Africa, where limited connectivity constrains data transfer from remote operations like mines to centralised data centres.

Unsurprisingly, specialised technology providers like 4Sight are witnessing the biggest growth in their data and AI divisions, with data governance, data science, ML, and AI-related training and ACM the areas receiving the most investment to drive innovation and meet rising demand.

The opportunity for Africa in this dynamic new world of work is the ability to leapfrog the rest of the world due to a lack of legacy infrastructure. The continent also boasts the world’s youngest population, many of whom will grow up alongside technology as AI natives. 

With the right training and infrastructure in place, Africa can capitalise on this demographic dividend to create a future-ready workforce that can effectively augment AI into their daily work and extract the potential of this transformative technology.

Tertius Zitzke, Group CEO at 4Sight Holdings Limited.

*** The views expressed here do not necessarily represent those of Independent Media or IOL.

BUSINESS REPORT