For ,聽a leading pan-African financial services group focused on emerging markets headquartered in South Africa, with a strong presence in 31聽countries,聽this transformation journey has accelerated over the past 18 months as the organisation expanded its focus beyond HR modernisation toward a broader cloud, data and AI-enabled human capital strategy.

, Group Human Capital: Chief Operating Officer at Sanlam, says the organisation鈥檚 approach balances immediate operational requirements with longer-term transformation objectives. 鈥淲e have adopted an ambidextrous strategy for our digital and data transformation journey, simultaneously exploiting operational excellence, proficiency and efficiency in our current landscape while exploring incremental innovation that enhances and elevates the user experience and driving our longer-term transformation journey 鈥� focused on leveraging intelligent, transformative technology to unlock business value.鈥�

A central focus throughout the implementation has been ensuring that transformation delivers tangible business value while also enabling the teams responsible for sustaining change. Sanlam is supported by a dedicated support structure for the programme that includes a technical centre of excellence team, programme management, change management, and business analysis capabilities.

鈥淭ransformation required us to approach change from multiple perspectives simultaneously. We always look at transformation through the lens of people, process and technology. One of the realities organisations face is that many people are not ready to embrace the pace of technological change, which makes change adoption and leadership sponsorship critically important.鈥� 

According to Bandyopadhyay, Sanlam鈥檚 broader transformation strategy spans several interconnected focus areas. 鈥淎 key priority being rebuilding our job architecture for relevance to the current and future workforce and more importantly to transition to a skills-based organisation. This will then unlock the opportunity for us to leverage SAP鈥檚 AI-enabled Talent Intelligence Hub which is the golden thread that links all talent practices to a skills currency.鈥�

The organisation has also prioritised the implementation of a cloud data solution, master data management and platform scalability as part of its effort to establish a more unified data core across the business. With multiple business entities operating across the group, standardising and scaling trusted workforce and operational data remains a significant strategic focus area.

, Group: Head of HC Tech and Talent Intelligence at Sanlam, says cloud adoption will continue to accelerate over the next two years. 鈥淲e are moving aggressively towards a cloud-first strategy, including payroll migration, data platform evolution, and broader business integration initiatives. Our focus is on how we build scalable platforms and data capabilities that position us for the future.鈥�

As part of this strategy, Sanlam is piloting -related capabilities and is progressing towards broader business data cloud initiatives planned over the coming years. The organisation is also exploring how 51风流Business Data Cloud, 51风流agents, and Joule capabilities can support orchestration, analytics, and employee-related workflows across the employee life cycle.

Alongside its platform modernisation efforts, Sanlam is re-evaluating core HR services and processes, including employee experience, employee relations, and document management, while strengthening its talent intelligence and people analytics capabilities to support better workforce planning and predictive decision-making. The Talent Intelligence function has matured significantly from reports and dashboards to trends, insights and predictive analytics. A key achievement has been the development of a solution to measure productivity across the various Sanlam business entities.

Intelligent automation is also playing an increasing role across areas such as service management, payments, compliance, and administrative HR functions, alongside the digitisation of compliance related scorecards like skills development to improve planning, monitoring and achievement of compliance targets. This has allowed Sanlam to service an increased customer base with a greater service offering at reduced costs.

Govindsamy says the transformation journey remains ongoing rather than a once-off implementation project. 鈥淭he next phase of our journey is focused on accelerating cloud propagation, strengthening analytics and data capabilities, and embedding intelligent automation more deeply into the business. Success depends not only on technology, but on sustained leadership sponsorship, adoption, and preparing the workforce for the future.鈥� 

, Managing Director for Southern Africa at SAP, says: 鈥淎s organisations modernise their workforce strategies, there is growing recognition that human capital transformation depends on more than digitising HR processes. It requires an integrated foundation that combines cloud, data, analytics and intelligent technologies to support better decision-making, stronger employee experiences, and greater organisational agility. Sanlam鈥檚 ongoing transformation journey reflects how forward-looking organisations are building scalable, future-ready HR environments that can evolve alongside changing business and workforce requirements.鈥�

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The Bellville Civic Centre in Africa now has a “digital twin,” a virtual copy that uses 1,200 sensors and a drone to watch everything in real-time. This smart system helps fix problems before they start, like finding leaky pipes or saving energy.聽It’s built for Cape Town’s exact needs, not just copied from Europe,聽and even helps with social issues and teaches people about upkeep. Now, this building can “talk” and help the city run better and save money.

What is a digital twin and how does it work?

A digital twin is a virtual model of a physical object or system, updated in real-time with sensor data. For Bellville Civic Centre, 1,200 sensors, a LiDAR drone, and a cloud physics engine created a digital replica, allowing real-time monitoring and predictive maintenance. This helps identify inefficiencies and potential issues proactively, optimizing building performance.

1. A Quiet Thursday That Changed Everything

The janitor鈥檚 clipboard still showed the same temperature columns, the electricians still argued about fluorescent tubes, and the leak in the basement still had to be fixed before the next council session. Yet, beneath this ordinary choreography, Bellville Civic Centre had quietly grown a second brain. Overnight, 1 200 credit-card-sized sensors, a spinning LiDAR drone, and a cloud physics engine 60脳 faster than real life stitched themselves into an invisible mesh. The concrete giant could now interrogate itself the way a doctor interrogates a heartbeat – asking, not just answering.

Inside the foyer, a Finnish suitcase snapped open. Out came matchbox fog-computing gateways, a stack of district-heating printouts from Helsinki, and – most convincing of all – signed data-sharing contracts with Nordic utilities that proved the jump from pilot to portfolio was already bankable. A projector threw the building鈥檚 new pulse onto the marble wall: cool blues for steady organs, warning reds for arrhythmias. One red vein leaked two-percent inefficiency from a chilled-water pump; another showed a third-floor zone that had spent three nights 0.4 掳C warmer than its set-point. A fire-exit sensor whispered that someone was forcing the door with three extra newtons – hinges beginning to seize.

In the old script those micro-clues would have become phone calls, Excel rows, and work orders already yellow with age. Now the digital twin ranks every intervention by life-cycle cost, authors its own weekly 鈥渕aintenance dance card,鈥� and beams it to handhelds. The deputy director tapped the red stairwell on the screen; instantly the model surfaced a 2024 actuator invoice, cross-checked the manufacturer鈥檚 mean-time-to-failure curve, and advised a swap before quarter-end. Predicted disruption: twelve minutes during a planned fire-system test. Likely downtime prevented: eleven hours. The Finns grinned; they had seen an Espoo courthouse cut annual energy use 18 % after only six months of the same ritual.

2. Built for Cape Town, Not Copy-Pasted from Europe

Espoo doesn鈥檛 stage blackouts; Cape Town does. Procurement here demands three quotes for anything above R2 000, and one depot may serve 250 scattered sites. So the architects tucked palm-sized, fan-less edge servers into electrical risers. When the fibre dies, these nodes keep a compressed, privacy-scrubbed clone of the twin alive, steering local loops: rooftop PV, battery UPS, smart-lighting relays. During outages, the conference wing stays lit on a 60 kWh buffer while corridors dim to 30 %, trimming 12 kW of peak without a human finger.

Sensor playlists are equally mixed. Some wings are 1970s concrete, others 1990s steel sheds, others brand-new mass-timber chasing net-zero. Thread, LoRaWAN and Wi-Sun radios chat in parallel; legacy breaker panels wear NFC tags that any TVET-college student can reflash in 90 seconds. Instead of marrying one vendor, the City hosts an 鈥淢-Bus to MQTT鈥� translator whose YAML recipes live on GitLab under Creative Commons. The only lock-in is curiosity.

Citizen privacy is engineered, not promised. Visitors renewing licences trigger anonymised heat-maps that forget faces after 900 seconds. Maintenance staff sign in with biometric fobs; an HVAC tech may raise a chiller set-point yet cannot unlock court archives. University researchers receive time-boxed API tokens that auto-expire without two-key renewal inside the firewall. The mantra is 鈥渟hare insights, not identities.鈥�

3. From Valves to Social Infrastructure – Ripple Effects No Spreadsheet Predicted

Borrowing from shipyards, the Finns gave every component a tamper-proof digital passport. Snap a photo of a corroded valve and the hash, signature, and timestamp lock into a private Ethereum fork. Smart contracts release micro-payment to the plumber only when AI vision confirms the fix. Early runs show disputed invoices down 35 % and warranty cycles shrinking from months to days. The building pays for proof, not promises.

Energy planning dives deeper than kilowatt dashboards. The twin ingests Time-of-Use tariffs, Eskom鈥檚 wind forecasts, and weather-service gust predictions to build a 72-hour optimiser. In a late-June rehearsal it slid 210 kWh from evening peak to pre-dawn, pre-cooling slabs and charging fleet EVs. Saved: R3 420 – one librarian鈥檚 annual salary when extrapolated across 70 facilities. Treasury is now modelling a green-bond tranche: a guaranteed 5 % energy cut could unlock R400 million for further retrofits.

Water joins the choreography. A 30 000-litre basement tank maps stratification layers, predicts Legionella risk, and diverts first-flush to sewer when rainfall tops 6 mm h鈦宦�. An ML model schedules irrigation only when evapotranspiration exceeds 3 mm and soil moisture drops below 22 %. Result: 46 % less potable water on landscaping, sparing 2.7 million litres – enough for seventeen households for a year.

Scaling is under way. Three libraries, two clinics, and the colossal Cape Town Civic Centre have already been LiDAR-scanned. The once-labyrinthine 51风流spreadsheet has collapsed into a lightning-fast graph database; planners can ask for 鈥渁ll coastal-zone boilers older than fifteen years that serve community halls with >30 % Saturday occupancy鈥� and receive a ranked replacement schedule linked to tender calendars.

Social infrastructure is next. Early-childhood centres with no in-house tech get a WhatsApp 鈥渕aintenance buddy鈥� that speaks isiXhosa voice notes. A caregiver photographs a flickering light; vision-recognition IDs the ballast and dispatches the nearest handyman. Where data is scarce, the bot reverts to one-cent USSD menus. Cape Town鈥檚 code is already tempting subtropical eThekwini and equatorial Singapore into south-south exchanges that outbid traditional donor loops.

4. A Living Curriculum for the City of Tomorrow

Every Thursday the disused records room becomes a 鈥淭win Lab.鈥� Failed circuit boards hang like hunting trophies, each annotated with failure mode and intern nickname. A live dashboard streams on the wall; if trainees trim another percentage point off weekly energy, the mayor tweets spinning wind-turbine GIFs. Maintenance is no longer an exile for the IT department – it is a badge for cleaners, clerks, councillors.

Occupants gamify stewardship. Guards hunt daylight sensors left in override, librarians chase dust alerts on HVAC grilles. Points buy canteen vouchers; the leaderboard hangs by the lift like a school sports chart. Behaviour bends faster than steel when feedback loops are witty and immediate.

If the roadmap hits 100 buildings by 2029, the City will have digitised 4.5 million square metres – Helsinki鈥檚 whole downtown. The next mayor will open one map and query every pump, lift, and luminaire in milliseconds. Finnish mentors now log into Cape Town servers to debug their own Espoo high-rises, admitting the student has become the server room. Between Bellville鈥檚 granite walls and Helsinki鈥檚 glass lecture halls pulses a new civic circulatory system whose language is open data, whose currency is kilowatts saved in real time, and whose winner is the resident breathing cooler air long before anyone knew the building had learned to speak.

What is a digital twin and how does it work at Bellville Civic Centre?

A digital twin is a virtual model of a physical object or system, updated in real-time with sensor data. For Bellville Civic Centre, 1,200 credit-card-sized sensors, a LiDAR drone, and a cloud physics engine were used to create a digital replica. This system allows for real-time monitoring and predictive maintenance, identifying inefficiencies and potential issues proactively to optimize building performance. It’s like giving the building a ‘second brain’ to interrogate itself and make smart decisions.

How is Bellville Civic Centre’s digital twin uniquely designed for Cape Town’s needs?

Unlike solutions simply copied from Europe, Bellville’s digital twin is specifically built for Cape Town’s environment, which includes factors like blackouts and specific procurement processes. It features palm-sized, fan-less edge servers that maintain a compressed, privacy-scrubbed clone of the twin during fiber outages, ensuring local operations like rooftop PV and smart-lighting relays continue. The system uses a diverse mix of sensor technologies (Thread, LoRaWAN, Wi-Sun) to accommodate various building types and avoids vendor lock-in by using an ‘M-Bus to MQTT’ translator with open-source YAML recipes.

How does the digital twin enhance maintenance and operational efficiency?

The digital twin significantly enhances maintenance by prioritizing interventions based on life-cycle cost, generating weekly ‘maintenance dance cards,’ and beaming them to handheld devices. For example, it can predict component failures, like a stairwell actuator, by cross-referencing invoices and manufacturer data, suggesting swaps to prevent downtime. This proactive approach has been shown to cut annual energy use significantly, as seen in similar implementations like an Espoo courthouse which reduced energy consumption by 18% in six months.

What are the ripple effects of the digital twin beyond building management?

The digital twin’s impact extends beyond basic building management to social infrastructure and financial benefits. It uses blockchain technology for tamper-proof digital passports for components, ensuring plumbers are paid only when AI vision confirms a fix, reducing disputed invoices. It also optimizes energy planning by integrating Time-of-Use tariffs, weather forecasts, and Eskom’s wind predictions to shift energy consumption and save costs. Furthermore, it optimizes water usage, reducing potable water for landscaping by scheduling irrigation based on precise environmental data. The system also supports social initiatives, such as a WhatsApp ‘maintenance buddy’ for early-childhood centers.

How does the digital twin project foster learning and community engagement?

The project includes a ‘Twin Lab’ where failed circuit boards are studied, and trainees are incentivized to reduce energy consumption, making maintenance a valued skill. Occupants are encouraged to ‘gamify stewardship’ by hunting for inefficiencies like overridden daylight sensors or dust alerts, with points leading to rewards like canteen vouchers. This approach fosters a culture of awareness and responsibility among building users and staff, effectively turning the building into a ‘living curriculum’ for the city’s future.

What is the future outlook and scalability of Bellville Civic Centre’s digital twin initiative?

The initiative is already scaling, with three libraries, two clinics, and the colossal Cape Town Civic Centre having been LiDAR-scanned. The goal is to digitize 100 buildings by 2029, covering 4.5 million square meters, equivalent to Helsinki’s entire downtown. This will allow city planners to query every pump, lift, and luminaire in milliseconds. The project has also garnered international interest, leading to ‘south-south exchanges’ with other cities like eThekwini and Singapore, demonstrating its potential as a global model for smart city development.

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AI is reshaping enterprise support and changing how solution providers think and operate, says Stefan Steinle, executive VP and head of global聽customer聽support at SAP, who adds that support has evolved into a strategic driver of business value.

Support in this context refers to services, management and resource allocation used to troubleshoot, address issues and optimise infrastructure within an organisation.

鈥淭he focus is on value generation and customer health,鈥� says Steinle. 鈥淪upport is central to driving business outcomes with AI-integrated platforms. Support teams are becoming more embedded in business strategy. They provide visibility into system performance, user behaviour and operational trends.鈥�

According to Steinle, AI-assisted toolchains and intelligent automation allow organisations to anticipate issues before they arise, streamline performance and improve long-term agility and resilience.

This is an entirely different approach to traditional support execution and application.

鈥淭raditionally, support operated on a break-fix model 鈥� issues were addressed when disruption occurred. AI changes this dynamic entirely. Through machine learning, pattern recognition and real-time data analysis, AI can continuously monitor systems, detect anomalies and predict potential failures before they impact operations. This enables preventive intervention rather than reactive troubleshooting.鈥�

AI is also improving decision-making, adds Steinle. 鈥淚t surfaces insights from vast datasets, identifies optimisation opportunities and recommends actions that improve performance, reduce costs and enhance user experience. In this way, enterprise support evolves from a technical necessity into a value-generating function that actively contributes to business strategy.鈥�

Shift from break-fix significant

AI expert and founder of AIforBusiness.net Johan Steyn says the shift from break-fix to strategic value driver is one of the most significant 鈥� and under-appreciated 鈥� transformations AI has enabled in organisations.

鈥淔or years, IT support was seen as a cost centre: reactive, ticket-driven and measured by how quickly problems were resolved. AI has fundamentally changed that equation. Predictive diagnostics, intelligent triage and automated resolution are not just making support faster 鈥� they are making it anticipatory. The best organisations are no longer waiting for things to break; they are using AI to understand system behaviour patterns and intervene before users are even aware of a problem,鈥� says Steyn.

The current status is one of rapid but uneven adoption, he adds.

Rise of autonomous enterprise

AI-assisted toolchains and intelligent automation are transforming ERP systems from static platforms into adaptive, self-improving environments.

According to Steinle, the shift is being driven by predictive maintenance capabilities, where AI analyses historical and real-time data to forecast failures and enable pre-emptive repairs. AI is also accelerating automated root cause analysis by identifying issues across complex system landscapes more quickly and accurately.

In addition, self-healing capabilities are enabling some system problems to be resolved automatically without human intervention, while AI-driven process optimisation tools continue to identify operational inefficiencies and recommend improvements.

The result is ERP systems that become more intelligent over time, enabling organisations to respond more rapidly to change, scale operations more effectively and strengthen operational resilience.

鈥淭he integrated toolchain breaks silos and drives collaboration between business and IT. You can confidently modernise your ERP landscapes while staying agile in today鈥檚 competitive climate,鈥� says Steinle.

鈥淎I plays a key role in enhancing capabilities by reducing errors and speeding up transitions. Take AI-powered change point detection as an example, where fundamental shifts in system downtimes can be found reliably and hence resolved faster. At the same time, AI-generated requirements reduce manual effort and accelerate the implementation process.鈥�

People and culture

However, Steinle warns that technology alone is not enough.

鈥淲hile technology is at the core of transformation, you can still fall short when it comes to outcomes if your people are not on board. When you continue to operate in old ways, the AI copilots or the automations are pointless. You get the same issues, but with more dashboards.鈥�

He adds that culture and leadership are critical to successful AI adoption. 鈥淎s they say, culture is what people do when no one is watching. Establishing this culture is what leadership is ultimately about. How motivated are your people? Are they as excited as you are about new innovations?鈥�

Diverse teams are also essential in solving problems within complex ERP environments.

Nazia Pillay, MD for 51风流southern Africa, adds: 鈥淭he next phase of AI adoption is about execution. Organisations are looking for trusted data foundations, strong governance and practical business use cases that can deliver measurable value.鈥�

Early stages

According to Steyn, larger, more mature organisations are already seeing measurable gains 鈥� reduced mean time to resolution, lower support costs and IT teams freed up for higher-value work.

鈥淏ut many organisations, particularly in markets like South Africa, are still in early stages, often constrained by legacy infrastructure and skills gaps. The outlook, however, is clear: AI-augmented support will become the baseline expectation, not a competitive differentiator,鈥� he continues.

Organisations that invest in this transition thoughtfully 鈥� with the right human capability alongside the technology 鈥� will build a genuine and lasting operational advantage, adds Steyn.

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The 2026 Future of Jobs Summit™ in Sandton did not begin with optimism. It began with urgency.

Held against the backdrop of, the summit brought together business leaders, policymakers, educators, innovators, investors, and youth voices at a moment when the country is confronting one of the deepest employment challenges in its democratic history.

The latest Quarterly Labour Force Survey (QLFS) released by Statistics South Africa paints a sobering picture: official unemployment has climbed to 32.7%, more than 8.1 million South Africans remain unemployed, and youth unemployment among 15鈥�24-year-olds stands at a devastating 60.9%.

But perhaps the most important insight emerging from the summit was this: South Africa cannot solve today鈥檚 jobs crisis with yesterday鈥檚 industries.

The global economy is reorganising itself at extraordinary speed around artificial intelligence, automation, renewable energy, digital services, biotechnology, advanced manufacturing, and entirely new forms of work and entrepreneurship.

New categories of jobs are emerging globally while traditional sectors face increasing disruption.

And yet much of South Africa鈥檚 national economic conversation remains anchored in the assumptions of the past. This is not simply a jobs crisis. It is a future-readiness crisis. That reality shaped the central focus of the 2nd Future of Jobs Summit™: Next10!, recognised in 2025 as an official T20 Side Event linked to South Africa鈥檚 G20 Presidency.

Rather than positioning itself as another conference filled with abstract policy discussions, the summit was designed as a national strategy platform focused on implementation, collaboration, and future industries.

Throughout the day, speakers repeatedly returned to one central theme: South Africa鈥檚 future competitiveness will depend on how quickly the country can align government, business, education, technology, and investment around scalable job creation ecosystems.

Gauteng MEC for Economic Development, Agriculture and Rural Development Hon. Vuyiswa Ramokgopa opened the summit by outlining how Gauteng is working to build a more inclusive growth economy capable of creating opportunities for young people.

Lance Williams, Public Sector Lead at 51风流South Africa, challenged delegates to rethink how technology and human potential can collectively rewrite South Africa鈥檚 economic story in the age of artificial intelligence.

Melvyn Lubega, Head of the Digital Service Unit in The Presidency, highlighted the growing importance of digital infrastructure and the digital economy in expanding pathways to employment and entrepreneurship for young South Africans.

One of the strongest messages emerging from the summit was that no single sector can solve the unemployment crisis alone.

The 2026 CEO Dialogue™, CHRO Dialogue™, and CMO Dialogue™ brought together business leaders, HR executives, and marketing leaders to discuss practical interventions around youth employability, leadership development, skills alignment, and industry collaboration.

Additional contributions from leaders such as Prof Bismark Tyobeka of North-West University, Marc Lubner of Afrika Tikkun, Faith Mangope of the Faith Mangope Technology & Leadership Institute, and Barry Hendricks of SASCOC reinforced the importance of education, technology, sport, and social innovation in building pathways toward employment and inclusion.

Importantly, the summit was not positioned merely as a discussion platform, but as the beginning of a longer-term national movement around future readiness and collaborative action.

Among the key outcomes announced were:

• The development of a Future Industries Report™ for national stakeholders;
• The creation of a Future of Jobs Charter™ co-authored by delegates;
• New collaboration pathways between business, education, government, and youth-focused organisations;
• Practical recommendations on youth employment, entrepreneurship, digital inclusion, and future skills development;
• A roadmap positioning South Africa as a continental hub for future industries and innovation.

But perhaps the summit鈥檚 most important contribution was psychological rather than technical. At a time when unemployment statistics dominate national headlines and pessimism increasingly shapes public discourse, the summit sought to reposition South Africa鈥檚 narrative from decline toward possibility.

Because despite the severity of the crisis, South Africa possesses many of the ingredients needed to compete in the future global economy: a sophisticated financial sector, globally respected entrepreneurs, expanding digital infrastructure, deep natural resources, world-class creativity, a strong tourism brand, and one of the youngest populations in the world.

What South Africa lacks is not potential. It lacks alignment.

One of the most powerful historical reminders referenced during the summit was South Africa鈥檚 preparation for the 2010 FIFA World Cup.

Between 2004 and 2010, the country created approximately three million jobs during a period of coordinated infrastructure investment, tourism growth, and national mobilisation.

The lesson remains relevant today: when South Africa aligns around a compelling national mission, progress accelerates. But the challenge facing the country now is arguably even greater.

South Africa is no longer competing only for tourists or investment flows. It is competing for relevance in a rapidly changing global economy increasingly shaped by technology, sustainability, innovation, and talent mobility.

Countries that fail to reposition themselves around future industries risk being left behind economically, technologically, and socially.

South Africa cannot afford to arrive late once again. Because ultimately, the future of jobs is not only about employment. It is about dignity. It is about inclusion. It is about restoring belief among millions of young South Africans that they still have a meaningful place in the future economy.

And perhaps the most important question raised by yesterday鈥檚 summit is this: Will South Africa continue defending industries of the past 鈥� or will it finally begin building the industries of the future?

Dr Nik Eberl is the founder and executive chair: The Future of Jobs Summit™ (Official T20 Side Event). He is also the author of Nation of Champions: How South Africa won the World Cup of Destination Branding).

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During panel discussions held at the Summit, it was revealed that the worsening unemployment crisis and the rapid rise of  are forcing business leaders, policymakers and youth advocates to confront an urgent reality: traditional approaches to job creation are no longer enough.

With youth unemployment among people aged 15 to 34 sitting at 45.8%, experts said the country must rethink how it prepares young people for a rapidly changing labour market increasingly shaped by technology, automation and digital skills.

Speaking during discussions focused on the future of work and employability in Africa, business leaders and youth development advocates stressed that collaboration between corporates, government and civil society will be critical to creating sustainable employment pathways.

, Chief Executive Officer of the , one of the panelists at discussions held during the Summit said connecting young people to opportunities and networks is one of the biggest challenges facing the country.

鈥淪kills become more powerful when young people are able to connect to people who can teach them and upskill them,鈥� said Gibbs.

She explained that many young South Africans face fear and uncertainty when trying to enter the workforce, particularly as AI transforms industries and career paths.

鈥淭here is so much fear in trying to find a job. It is all of us that need to do something different,鈥� she said. 鈥淐onnecting skills with opportunities is what we need to look at and AI is a fantastic tool to help you with creating and opening up that conversation.鈥�

Gibbs added that behind the unemployment statistics are real people and communities struggling to find stability and opportunity.

鈥淏ehind these figures there are faces, names and stories,鈥� she said.

They further argued that while AI is often viewed as a threat to employment, it also presents significant opportunities for those willing to adapt and learn new skills.

,聽51风流Young Professionals Graduate (YPP), Global Government Affairs & CSR Intern at SAP, said fears around AI replacing jobs often stem from resistance to change.

鈥淭he notion of AI taking jobs comes from the notion of not willing to learn,鈥� Motseta said. 鈥淲e need to learn and adopt as it can assist in daily work lives.鈥�

She encouraged young people to invest in understanding AI and digital tools in order to remain competitive.

鈥淲e should be investing in learning more about AI and to remain up to date,鈥� she said.

During a panel discussion under the banner:聽Creating Jobs in the Age of AI,聽,聽a senior solution advisor and AI specialist at 51风流said聽organisations and individuals alike need to embrace a mindset shift around reskilling.

鈥淚f we do not come to terms that we need to adapt and reskill, people who are willing will not be left behind,鈥� Sevel said.

The discussions also highlighted the widening digital and skills gap facing corporate South Africa.

, 鈥檚 Tech Consulting Leader and Tech Alliances Leader said many technology firms and banks are already facing ageing skills gaps and increasing demand for digital talent.

鈥淢ost tech and banks have an ageing skills gap,鈥� Shaun said. 鈥淚t requires people to think differently and work together.鈥�

He added that stronger collaboration between businesses is needed to scale meaningful employment interventions.

鈥淔orums such as these are exceptional. We need more corporates in the room with more commitments made,鈥� he said.

The role of infrastructure in enabling long term job creation also emerged as a major theme.

, Head of the Digital Service Unit in the Presidency and chairperson at the , argued that sustainable job creation depends on building strong digital infrastructure rather than relying solely on companies to create jobs directly.

鈥淛ob creation does not come from companies. It comes from infrastructure,鈥� Lubega said.

He pointed to countries such as India, where investment in digital infrastructure unlocked innovation and large scale economic participation.

鈥淪outh Africa has good foundations, a strong banking sector, strong institutions and incredible talent,鈥� he said. 鈥淏ut everyone is working in their own silos and we need to come together and collaborate.鈥�

Executives from聽聽also stressed that Africa鈥檚 future workforce will need to adapt rapidly as industries evolve.

, Managing Executive: TalentManagement and Transitions at Absa Group, said Africa鈥檚 future growth story depends on decisions being made now around skills development and employability.

鈥淭he decisions we make every day shape the continent,鈥� Bako said. 鈥淲e need to build the skills of the future and create sustainable jobs.鈥�

According to the World Economic Forum, roughly 60% of Africa鈥檚 workforce will need reskilling in the coming years as technology reshapes industries and business models.

, Chairperson and CEO, warned that the speed of change is leaving many young people underprepared for the realities of modern work.

鈥淭he change that is taking place is chaotic and we are not necessarily equipping young individuals for what is out there,鈥� Mark said.

He argued that businesses, and civil society organisations need to work more closely together to understand the realities facing young communities.

鈥淐ivil society lives on the streets. They have a deep understanding of what the young community wants,鈥� he said.

Amanda Gibbs, Chief Executive Officer of the African 51风流User Group, one of the panelists at discussions held during the Summit said connecting young people to opportunities and networks is one of the biggest challenges facing the country.

鈥淪kills become more powerful when young people are able to connect to people who can teach them and upskill them,鈥� said Gibbs.

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鈥淲ill 51风流actually be a software company in the future?鈥�

It鈥檚 not the kind of question the CEO of a software company would usually ask thousands of customers, partners and analysts. At Sapphire 2026, SAP鈥檚 annual conference held this month in Orlando and Madrid, CEO Christian Klein asked his audience if they were scared by the question.

鈥淚鈥檓 not scared,鈥� he answered himself. 鈥淔or me, the time right now is the beginning of something even better.鈥�

The conference saw the launch of SAP鈥檚 Business AI Platform, a unified environment for building and governing AI agents across enterprise operations, grounded in real business context.

The strategy is to enhance critical business workflows, so that humans and AI work together to meet the accelerating demands of global business.

鈥淎ccording to a recent Stanford AI survey, almost every company is now using AI, but many see only little value,鈥� said Klein. 鈥淲hy do we face such huge challenges with AI in business? At the top of this iceberg, visible to everyone, is that large language models are getting better and better at tasks like generating text or images or in specific domains like writing software.

鈥淎ll of these use cases are related to publicly available content the modules are trained on. But if you go below the waterline, beyond the level of sales demos, and into the real business world, you鈥檙e going to find out that none of these models are trained on your business data and processes.

鈥淭hese AI agents also don鈥檛 naturally adhere to governance requirements, like your security compliance framework, your data privacy requirements, or to your company鈥檚 identity and authorisation rules. All AI agents 鈥� have faced these challenges until now.鈥�

The solution, he suggested, was that a company鈥檚 enterprise resource planning system, or ERP, should be recognised as the brain of every business. Since 51风流is world leader in ERP software, one might argue, naturally the CEO would say that.

But Klein made a good case for it: 鈥淔or over 15 years we have been developing an ERP with incredibly deep process and data domain know-how. On top of that, all your governance requirements and customer-specific extensions are stored in the ERP. The ERP is the trusted system of execution running your company.鈥�

Powerful external validation came from Anthropic, the company behind the Claude family of AI models, and that is competing neck and neck with Open AI to become the most valuable AI platform company in the world. At Sapphire, 51风流shared video testimony from Anthropic co-founder and president the Daniela Amodei in which she declared: 鈥淭he world鈥檚 largest enterprises run on SAP. That鈥檚 exactly where trusted AI belongs.鈥�

That significance of this alignment revolves around the core value proposition of the Business AI Platform: trustworthiness.

JPMorgan Chase CFO Jeremy Barnum, who joined Klein on stage in Orlando, said his bank was already running agents in production on SAP, operating within defined compliance boundaries.

鈥淭he agents that we鈥檝e built are not inventing their own business rules,鈥� he said. 鈥淭hose rules rather come directly from 51风流Embedded Control Framework, and every AI-driven intervention is logged and fully traceable.鈥�

One organisation鈥檚 production deployment does not establish a category. But the compliance architecture it describes is precisely what most organisations attempting enterprise AI have not yet achieved.

Jensen Huang, CEO of $5-trillion AI chipmaker Nvidia, also appeared in a pre-recorded video segment, making it clear that AI agents would not replace ERP. The most ringing endorsement? Nvidia itself used 51风流as its ERP brain: 鈥淲hat 51风流and Nvidia are building together is one of the most important platforms in enterprise AI. Nvidia鈥檚 supply chain is incredibly complex. Millions of parts, hundreds of partners and factories, all connected through SAP. But what鈥檚 changing is not just how enterprise systems are managed, it鈥檚 how work actually gets done.

鈥淲e鈥檙e moving from hand-coded software to AI that can understand, reason, and act. AI no longer simply answers questions. It works for you. And enterprise systems are where work happens. Finance, supply chains, procurement, and every workflow in between.

鈥�51风流is the foundation of enterprise. And now they鈥檙e building the agents that sit on top of it, trained on proprietary data with the skills to act. Soon, every company will have a workforce of agents. These specialised agents will not replace enterprise software. They will make enterprise software more powerful than ever.鈥�

* Arthur Goldstuck is CEO of World Wide Worx, editor-in-chief of , and author of 鈥淭he Hitchhiker鈥檚 Guide to AI 鈥� The African Edge鈥�.

This article first appeared in .

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鈥淔or the mission-critical processes of our customers, 鈥榓lmost right鈥� just isn鈥檛 good enough,鈥� says Christian Klein, CEO of 51风流SE. 鈥淏y uniting 51风流Business AI Platform with 51风流Autonomous Suite, we anchor AI agents in the business processes, data and governance so they can deliver accurate, compliant and secure outcomes 鈥� unlocking new sources of revenue and meaningful cost savings.鈥�

The Autonomous Enterprise includes a unified AI platform for building, contextualising and governing agents, an autonomous suite that executes core business operations and a new user experience that redefines how people work with enterprise software.

Introducing 51风流Business AI Platform

51风流Business AI Platform is a new foundation for building and deploying enterprise AI grounded in real business context. 51风流Business AI Platform now unifies 51风流Business Technology Platform, 51风流Business Data Cloud, and 51风流Business AI into a single, governed environment.

At its core is the 51风流Knowledge Graph solution, which gives AI agents a structured map of business entities, processes and relationships across a customer鈥檚 51风流landscape. Joule Studio is SAP鈥檚 AI-first solution for building enterprise agents, applications and agentic workflows. Developers can build using the no-code, pro-code, and AI frameworks of their choice on SAP-managed infrastructure that is secure, scalable and optimised for enterprise AI.

Building on this foundation, 51风流also introduced 51风流Autonomous Suite which enables SAP鈥檚 existing business applications with AI agents capable of running processes from start-to-finish.

The suite will deploy more than 50 domain-specific Joule Assistants across finance, supply chain, procurement, human capital management and customer experience. These assistants will automate end-to-end processes by orchestrating a subset of over 200 specialised agents to execute precise tasks. For example, the new Autonomous Close Assistant can compress the financial close process from weeks to days by automating journal entries, reconciliation, and error resolution across the entire process.

51风流also launched Industry AI, expanding its deep industry portfolio through seven autonomous solutions that will enable start-to-finish industry processes and embed sector-specific process logic, data models and regulatory requirements.

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Since 2020, the continent has seen meaningful investment in logistics infrastructure. The African Development Bank committed , while Africa50 deepened its role in financing trade-enabling infrastructure. Ports have been one of the clearest focal points. Nigeria鈥檚 Lekki Deep Sea Port is emerging as a serious regional node. South Africa鈥檚 Cape Town and Ngqura ports have posted notable improvements in performance after years of decline, while Transnet has clawed back some operational ground through better turnaround times and improved crane productivity.

Throughout Africa, governments have invested in ports, rail and trade corridors, and the Africa Continental Free Trade Area (AfCFTA) has started to turn the long-discussed idea of regional trade integration into something more tangible. In pockets across the continent, the results are faster cargo movement, stronger port performance, growing intra-African trade, and a more serious push toward localisation in sectors ranging from manufacturing to health.

AfCFTA notably helped push intra-African trade to $220.3 billion in 2024, , following a sharp jump in the number of countries actively trading under the agreement. However, it remains a work in progress instead of a finished shield, with tariff schedules, digital trade protocols, customs harmonisation and non-tariff barriers still being worked through.

Test of resilience

The question now is whether the progress made within the continent鈥檚 supply chains has delivered the resilience to withstand repeated shocks. The Red Sea crisis, now stretching into its third year, has already forced a major restructuring of Asia-Europe-Africa shipping. The near closure of the Strait of Hormuz has layered a second and more acute shock onto already strained global trade flows.

For African economies, the effect is being felt all at once through higher freight costs, longer lead times, elevated fuel prices, fertilizer disruption, and tighter access to trade finance.

Agriculture is especially exposed. A significant share of Africa鈥檚 fertilizer imports comes from Gulf producers, with East and Southern Africa particularly reliant on those flows. Disruption in Hormuz raises shipping costs, and threatens planting cycles, food production, and ultimately food security. Constricted fertilizer supply drives up costs, with the shock moving quickly from ports and tankers into farms, food prices, and household budgets.

Africa鈥檚 trade finance gap creates additional challenges. When lead times become unpredictable, businesses carry more buffer stock. Cost increases for fuel, freight and insurance drives demand for greater working capital. When banks remain cautious and access to formal trade finance is limited, especially for SMEs, resilience becomes something only the largest firms can afford.

This is why the next phase of supply chain resilience in Africa cannot be built only with cranes, roads, and policy frameworks, but with better visibility, greater efficiency, and improved decision-making.

A connected supply chain

Greater digitalisation is one of the most encouraging developments since the pandemic. Digital customs systems, single windows, electronic cargo tracking, and trade portals are reducing friction at the border.

In markets where customs and border processes have been digitised, . Digital trade facilitation has already shown what practical resilience looks like: less paperwork, better visibility, fewer delays, and more predictable movement of goods.

Digital platforms, AI-enabled forecasting, and scenario modelling have become more than technology talking points. In a volatile operating environment, end-to-end visibility is the difference between reacting late and acting early. Companies need a clearer view across suppliers, logistics partners, inventory, transport routes, and cost exposure. They need to test disruption scenarios before they happen, and model the impact of rerouting, delays, fuel spikes, or supplier failure in real time.

This is where embedded AI and better workflow orchestration are starting to matter. The real value is not automation for its own sake, but the ability to guide decisions in real time, coordinate actions across previously disconnected functions, and keep the wider value chain in sync as conditions shift. In practice, that means breaking down long-standing silos between planning, procurement, production, logistics, and finance so that businesses can respond faster, allocate resources more effectively, and maintain service levels under pressure.

In an , supply chain leaders cited advanced analytics and AI as their most important technology investment over the next three years. The top expected benefits of embedding AI into supply chain planning processes were improved decision-making, supplier selection, and inventory optimisation.

For African businesses, governments, and logistics operators, the lesson of 2026 is not that resilience investments have failed, but that more is needed to be done. Over the next five years, the continent鈥檚 supply chain challenges will go beyond simply building greater resilience to connecting what has been built into a system that can withstand a volatile, unpredictable world.

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Pierre du Plessis, strategist and founder of Be Brave, and the event鈥檚 guest speaker, explored how trust, culture and meaningful engagement can transform teams and communities, touching on the  of 鈥榯ribes鈥� – small, connected groups where people feel seen, trusted and valued. 

鈥淧rofit and growth are lagging indicators of deep chemistry, not ,鈥� he told attendees. 鈥淭he board may set a strategy, but the tribe makes it real. Only the tribe builds the movement.鈥�

Through storytelling and practical examples, Du Plessis illustrated why connection matters more than metrics alone, and why shared experiences are valued over shortcuts. 

鈥淭rust is fundamental to any team,鈥� he explained. 鈥淚t enables conflict, commitment, accountability and ultimately meaningful outcomes.鈥�

Research highlighted at the session reinforced these insights. Gallup studies show that, globally, only 21% of employees feel truly engaged at work, while actively disengaged employees can undermine entire teams. Loneliness and over- in organisations not only erode morale but also have measurable influences on productivity and wellbeing. 

鈥淗umans are pack animals,鈥� Du Plessis emphasised. 鈥淲e thrive in communities, not in isolation.鈥�

The session also explored the concept of meaning and transcendence at work. Drawing from examples ranging from Trappist monks to special needs teachers, Du Plessis argued that fulfilling work is about impact, not just a pay packet. 鈥淭hese Belgian monks produce some of the world鈥檚 best beer,鈥� he said, 鈥渂ut their purpose isn鈥檛 profit, it鈥檚 sustaining the community. Meaning  performance; profit is a side effect.鈥�

As organisations grapple with digital transformation and AI-driven workflows, this message resonates: human connection remains a competitive advantage. This philosophy is also shaping AFSUG鈥檚 own strategic direction.

鈥淎t AFSUG鈥檚 local 51风流user conference, SAPHILA, last year, we spoke about  our community and establishing our tribe, and this is exactly what we鈥檙e doing as an organisation,鈥� explained Amanda Gibbs, AFSUG CEO. 

鈥淎FSUG has reached an inflection point 鈥� one where we鈥檝e looked back at why the organisation was originally founded: as a peer-to-peer customer networking platform that helps customers bridge the gap with SAP. We are now  a path towards a community that is purpose-led, operationally sound and designed for  impact across .

鈥淭he shift we are putting into place is to move away from being event-driven, reactive and purely informational, towards becoming outcomes-driven, influential and insight-led. The pivotal role that AFSUG must play is as the trusted voice of the African 51风流community and an independent advocate.鈥�

AFSUG chairman Duke Mathebula echoed Gibbs鈥� statement, adding that the organisation is committed to action, structured advocacy and creating real, measurable value for the local 51风流community, as well as empowering transformation.

鈥淭rue impact comes from creating tribes of engaged, courageous and committed people who can make a real difference, and this is exactly how AFSUG plans to move forward,鈥� he said.

The post Why Trust and 鈥楾ribes鈥� Still Matter in an Age of Metrics appeared first on 51风流Africa News Center.

For much of the past decade, AI has lived in labs, pilots and PowerPoint decks. The next phase is different. AI is moving into the operational core of organisations, reshaping how decisions are made, work is executed and value is created.

AI is becoming the most significant technology shift enterprise leaders will face in this generation. Not because the algorithms are new, but because the operating model required to make AI work at scale is fundamentally different.

One of the clearest changes heading into 2026 is the move from AI that assists humans, to AI that acts on their behalf.

Early enterprise AI tools functioned as copilots: surfacing information, generating insights or suggesting next steps. Increasingly, organisations are deploying autonomous AI agents that recommend actions 鈥� and take them 鈥� executing multi-step business processes within defined roles and controls.

This transition matters because it forces leaders to confront new questions of trust, accountability and governance. Autonomous AI can deliver significant productivity gains, but only if organisations are prepared to define where machines can act independently, where human approval is required, and how exceptions are handled.

In practice, this means treating AI agents less like software features and more like a digital workforce: assigned roles, clear permissions, monitored performance and escalation paths when things go wrong. Without this discipline, autonomy becomes risk rather than advantage.

Intelligence must be built in, not bolted on

Another defining trend is the move toward AI-native systems. Many organisations still treat AI as an add-on: a layer of intelligence bolted onto processes designed decades ago. That approach is reaching its limits.

AI-native architecture embeds intelligence directly into core workflows, allowing systems to understand intent rather than simply execute transactions. Instead of navigating complex menus and dashboards, users express what they want to achieve, and systems orchestrate the necessary steps across functions.

For leadership teams, this is not a user-interface upgrade, but a shift in how work gets done. Ideally, decision-making accelerates, organisational friction reduces, and the boundary between analysis and execution begins to disappear.

However, this only works when underlying systems are clean, standardised and integrated. Which leads to a harder truth many organisations are discovering.

Data quality is the real AI constraint

The biggest barrier to AI success is not model sophistication, but data reality. AI systems amplify whatever foundations they are given. Clean, consistent data produces reliable outcomes, while fragmented, poorly governed data produces confident nonsense.

This is why data has become the strategic nervous system of the modern enterprise. AI depends on shared definitions of customers, products, suppliers and processes. It requires transactional integrity, accessible historical context and the ability to combine internal and external information in real time.

Organisations that have postponed data discipline are finding that AI exposes weaknesses instantly, often in ways that affect customers, regulators or financial performance. In the year ahead, leaders will increasingly be judged on whether they treated data as a strategic asset early enough, rather than as an IT hygiene issue.

Closely linked to data readiness is a simple but central principle: keeping core enterprise systems clean.

Years of excessive customisation have left many organisations with fragile ERP environments that are difficult to upgrade and harder to integrate with modern AI capabilities.

The shift toward standardised cores with extensions built outside the core system creates an environment where innovation doesn鈥檛 break operations.

For boards and executive teams, this requires a mindset shift. Standardisation is not a loss of competitive differentiation, but the price of adaptability. The differentiation moves to how organisations use data, design experiences and make decisions, not how many lines of custom code they maintain.

Technology alone will not deliver results

Perhaps the most underestimated factor in AI success is change management, which consistently accounts for a larger share of AI outcomes than technology itself.

AI changes roles, not just tools. Finance teams move from processing transactions to managing exceptions. HR shifts from administrative workflows to skills intelligence.

Operations leaders rely more on forecasts and simulations than static reports. These changes demand new skills, new incentives, and new ways of measuring performance.

This year, leaders must invest in adoption with the same commitment and focus as they invest in new capabilities. AI literacy should be a core leadership competency not just a specialist function.

As AI initiatives multiply, so does the risk of fragmentation. Different business units experimenting independently can create inconsistent standards, duplicated effort and unmanaged risk.

This is why many organisations are establishing AI centres of excellence that coordinate AI innovation. Effective governance frameworks address five questions: how AI systems are approved and retired, how decisions are logged and audited, how policies are enforced, where human oversight is required, and how performance is measured.

In 2026, AI governance will be viewed much like financial governance: a prerequisite for trust, not a brake on progress.

From pilots to production or paralysis

A final challenge looms large: scaling. Many organisations are stuck in what has become known as 鈥減ilot purgatory鈥�, where successful experiments never reach enterprise impact.

The reasons are consistent: poor integration with core systems, unclear ownership, lack of user trust, weak data foundations and vague ROI metrics. Moving from pilot to production requires deliberate planning, phased rollout and visible executive sponsorship.

Leaders who expect AI to scale itself will be disappointed, while those who design for scale from day one will pull ahead quickly.

As we accelerate into 2026, AI is an operational reality. The real strategic question for leaders is whether their organisations are structurally ready for AI, with clean systems, trusted data, skilled people and disciplined governance. With these foundations, AI becomes a durable source of advantage.

In a volatile global environment, leadership is increasingly defined by the ability to move forward without perfect certainty. Business AI, deployed responsibly and at scale, is becoming one of the most powerful tools leaders have to do precisely that.

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