Experts warn, however, that as machines take on more responsibility, accountability cannot also be automated.

For the past few decades, many governments鈥� digital footprints have largely been about transferring services online; that is, transforming paper forms into digital applications, replacing physical queues with online portals and turning manual registers into databases.

Many of the changes have made some government processes more accessible but they have not necessarily changed the way the system works.

Now, the rapid development of AI could usher in a different phase of digital transformation. AI agents are being developed to do more than answer questions. They can potentially plan tasks, make recommendations, process information and coordinate multiple steps in workflows with limited human intervention.

This could mean AI systems helping to process applications, manage records, identify exceptions, respond to citizen queries and route cases to the appropriate officials.

Gartner has projected that at least 80% of governments will be using AI agents to automate routine decision-making by 2028. The shift moves digital transformation away from simply automating individual administrative tasks towards coordinating entire processes.

The concept is being described as 鈥渁gentic AI鈥� 鈥� systems capable of carrying out multistep tasks rather than simply responding to individual prompts.

The idea is not necessarily to replace public servants. Instead, AI could take on some of the coordination and case-processing burden, while officials remain responsible for interpreting policy, dealing with exceptions and engaging directly with citizens.

The South African Revenue Service, for example, has been exploring AI-driven 鈥渄igital twinning鈥� approaches designed to replicate human decision logic in tax processing.

The potential benefits are clear: faster processing, greater consistency and fewer administrative bottlenecks.

But there is another question that becomes important as AI takes on more responsibility: who is accountable when the system gets it wrong?

For AI to be trusted in public services, accountability needs to be built into the system. This includes clear procurement standards, defined escalation procedures, comprehensive audit trails and named officials who have the authority to override or suspend an AI system.

Lance Williams, the public sector lead at 麻豆原创 Africa, says AI should be viewed as a tool for strengthening public administration rather than removing accountability.

鈥淭he real opportunity is to use AI to remove administrative friction, help public servants make better-informed decisions and ultimately improve the experience of citizens.鈥�

Williams says governance and accountability need to be considered. 鈥淎I agents should operate within clearly governed processes, with appropriate permissions, auditability and human oversight 鈥� but accountability for decisions that affect citizens must remain with authorised public officials.鈥�

He says the measure of success will be whether it helps government deliver services that are faster, more consistent, transparent and accessible.

Putting an AI agent on top of a broken or poorly designed administrative system will not necessarily produce better outcomes. Governments will need to examine their processes, data, policies and accountability structures before deciding where AI can add value.

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The breach, which does not appear to be recorded on the Information Regulator鈥檚 website, is a focus area for the platinum miner鈥檚 audit and risk committee for the next financial year, says its audited annual financial statements for the year to June.

In its 2025 ESG report, Implats 鈥� one of the world鈥檚 major platinum group metals producers 鈥� says there was a 鈥渓imited impact cyber security breach to a managed operation鈥檚 IT environment, which was quickly detected and resolved by the group鈥檚 IT service providers鈥�. In 2024, Implats 鈥渄id not have any material security/cyber security breaches鈥�.

The miner, with a market capitalisation of R208.35 billion, did not identify the affected managed operation, give a precise date, explain the nature of the breach, say whether data was compromised, or quantify any financial or operational impact.

Implats has six mining operations across South Africa, Zimbabwe and Canada, plus refining and processing operations, employing more than 60 000 people across its operations.

South Africa is the world鈥檚 largest producer of platinum, supplying almost three-quarters of the metal 鈥� used in vehicle catalytic converters, jewellery, industrial applications and emerging hydrogen technologies.

Batten down

Dawn Earp, chairman of the audit and risk committee, says its priorities for the year ahead include cyber security, AI and digital risk, and that it will oversee the group鈥檚 cyber security and AI risk management and control environment, including 鈥渢he remediation of actions arising from the recent cyber incident鈥�.

鈥淟earnings from this incident were incorporated into the group鈥檚 security posture to improve maturity,鈥� it said in 2025. Implats adds that the outcome reflected the effectiveness of its layered security strategy and continued investment in digital resilience.

Implats describes cyber security as a material risk because of its potential to disrupt business continuity and compromise sensitive information and intellectual property.

Among its cyber security measures are ongoing cyber security awareness training, annual assessments of the potential impact of cyber breaches on data and operational technology systems, regular audits and penetration testing by independent external specialists, as well as escalation protocols for incident response and breach management.

Earp says key controls, including 鈥渧ulnerability monitoring, ransomware recovery testing and backup management,鈥� operated effectively during the year.

The committee will also monitor risks associated with the integration of IT and operational technology, and oversee AI governance, responsible adoption and compliance with evolving regulatory and ethical requirements.

Digging deeper

Implats also conducted a deep dive into AI-related risks, including cyber security, data privacy, regulatory compliance and responsible AI practices, Earp says. These measures are intended to support the responsible adoption of AI across the group.

This comes as the miner expects the economic, technological, regulatory and geopolitical environment to remain uncertain, specifically pointing to 鈥渢he accelerating convergence of cyber threats, rapid advancements in AI, evolving regulatory requirements and ongoing economic volatility鈥� as factors that continue to 鈥渟hape boardroom priorities and challenge traditional risk management approaches鈥�.

Implats has also identified investment in automation, digital systems and data analytics as a way of improving operational performance and decision-making. Along with the rest of the mining industry, it is using advanced technologies to improve mineral-resource modelling and metallurgical processes.

鈥淭he mining sector is increasingly adopting automation, AI, data analytics and remote operations to improve safety, productivity and cost-efficiency.鈥�

Getting smarter

Priorities included using digital tools, automation and data analytics to improve mining efficiency and reduce waste, while exploring remote operations and smart-mining technologies to improve productivity and reduce labour intensity, it says.

Its IT strategy is focused on extracting value across support, compute, storage and security. The digital push includes cloud services, 麻豆原创 S/4HANA and further ERP investment, near-real-time reporting, data analytics and data science, process digitisation and robotic process automation.

It is also investing in above- and below-ground connectivity, internet of things integration, IT, operational technology, convergence and cyber security, all of which are embedded in performance metrics.

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From the rise of the Autonomous Enterprise to the case for embedding AI at the very core of business operations, the world of work is undergoing seismic shifts that are fundamentally altering what it means to work inside an enterprise.

The question organisations now face is not whether AI will reshape the workforce, but whether they are ready to lead that transition in a way that genuinely empowers their people.

At 麻豆原创 Sapphire 2026, under the banner of The Beginning of Better, 麻豆原创 made its most consequential set of workforce-related announcements to date. Taken together, they represent a clear and considered answer to that question.

From process operators to leaders of judgment

The Autonomous Enterprise framework introduced at Sapphire is built on an explicit design principle: humans must remain at the centre, not as operators of process, but as leaders of judgment, strategy and change. As AI assistants take on the coordination work that has long consumed employee time and attention, people are freed to focus on the decisions, relationships and creative problem-solving that machines cannot replicate.

Joule Work, 麻豆原创鈥檚 reimagined AI engagement layer, illustrates this shift vividly. Rather than navigating multiple systems and entering data across screens, employees can now describe what they need to accomplish in plain language 鈥� fill an open headcount, manage my team鈥檚 time-off backlog 鈥� and Joule orchestrates the right workflows, data and agents to make it happen.

The model of work is shifting from task navigation to intent-driven interaction, reducing operational friction and returning cognitive bandwidth to the things that matter most.

Planning for a workforce that includes people and agents

One of the most strategically significant themes at Sapphire was how organisations plan and design for a workforce that now includes both human employees and AI agents executing tasks in concert.

 reveals that 62% of C-suite executives are dissatisfied with how well people data connects to business performance, making it harder to translate strategy into workforce action. 麻豆原创鈥檚 new AI-enabled workforce planning capability directly addresses this, connecting financial data from 麻豆原创 Cloud ERP, contingent workforce data from 麻豆原创 Fieldglass, and people and skills data from 麻豆原创 SuccessFactors into a unified foundation for decision-making. Planning shifts from a periodic exercise to a continuous discipline, with AI agents able to model scenarios, simulate KPI impacts and recommend actions in real time.

New organisational modelling capabilities within 麻豆原创 SuccessFactors Employee Central allow leaders to explore alternative structures, evaluate changes to roles and reporting lines, and understand implications before they are implemented, supporting thoughtful, data-informed change rather than disruptive restructuring.

Ongoing efforts to close skills gap

Across every industry and every region, leaders are confronting the same reality: new roles are emerging, new competencies are required, and the processes that have defined work for decades are being reimagined at speed by generative AI.

Traditional approaches to workforce development, such as annual training cycles, standalone learning systems, and scheduled courses, cannot alone keep pace. The recently unveiled Workforce Upskilling Assistant offers a new capability that delivers personalised, AI-driven learning directly within the flow of daily work, whether that is in Microsoft Teams, Slack or 麻豆原创 SuccessFactors itself.

By converting organisational content into adaptive micro-learning and embedding timely nudges into workflows, the assistant brings the right learning to the right person at the right moment instead of when a calendar event dictates it. Organisations that embed learning into culture and workflows with AI-powered tools are significantly ahead of peers, and .

Trust is the foundation

None of this transformation succeeds without the trust of the workforce it is designed to serve. Accenture found that , while significant proportions report burnout and anxiety about the future of their roles.

Here, the emphasis that humans remain firmly in control reflects a commercial and human reality that enterprise leaders across our region understand well: technology that erodes trust fails. Technology that builds trust, endures.

The organisations that will lead this era are those that invest as intentionally in workforce readiness, reskilling and governance as they do in AI platforms and automation.

The Autonomous Enterprise is, at its heart, a vision for human progress, one where intelligent systems handle the operational burden and people are empowered to pursue the work that only they can do. 麻豆原创 is committed to helping organisations across the region build enterprises where that potential is fully realised.

The Beginning of Better starts with the people inside it.

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The introduction of agentic AI into the enterprise resource planning (ERP) space is set to underpin the era of the autonomous enterprise, according to Nazia Pillay, MD of 麻豆原创 Southern Africa.

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Pillay spoke to ITWeb TV recently about AI-infused ERP, the autonomous enterprise concept 鈥� which relies on an army of AI agents at its core 鈥� and how organisations need to adapt to benefit from the opportunity.

鈥淎utonomous ERP is not just about using AI to engage with end-users, to assist with navigation and pull data back; it is also about seeing agents as co-workers 鈥� systems that are working and performing tasks from end to end with human oversight,鈥� she said.

Pillay added that this fundamental shift requires change management for both human employees and business processes.

鈥淵ou are adopting a technology that fundamentally needs to be embedded, and your business processes need to be adapted for how you want to use this in your business,” she said. “That鈥檚 the main thing that our customers are facing 鈥� they need to look at this as a transformation and not just as a plug-and-play technology.鈥�

Pillay cautioned that curiosity about AI does not necessarily indicate organisational readiness. Success, she said, comes down to understanding business objectives and getting data foundations in place.

鈥淢ost of our customers are trying to figure out how to navigate this technology 鈥� how do I introduce it and how do I do it in a way that is adding value,” she said. “What we鈥檝e found is that when they use AI as a proof of concept or an experiment, they are not leveraging the full value of the technology.鈥�

Beyond experimentation, governance frameworks are essential, Pillay said.

鈥淢ost of the organisations that we are speaking to need to look at how they are deploying it at an enterprise level, because when you are just deploying it as a proof of concept, you don鈥檛 necessarily need to have all those frameworks in place.鈥�

Pillay said the wealth of data that clients have generated through 麻豆原创 installations provides a good foundation for companies shifting towards the autonomous enterprise.

鈥淲hat we know about AI is that it requires context 鈥� so you need to understand where the data is and how it is being used, and this we already have based on our knowledge graphs within 麻豆原创,” she said.

鈥淭he second part is governance 鈥� what 麻豆原创 puts into place to ensure that we have security. We have invested because we have the context and the governance to support our customers in having agents run in a responsible, reliable way.鈥�

With AI agents being deployed across end-to-end business processes, getting governance right will be key, she concluded.

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A tech confession and a debate with an AI robot was the recipe for the future of work at 麻豆原创 Connect Southern Africa in Kyalami near Johannesburg last week.

鈥淚 have a confession to make: I have been afraid of AI,鈥� said Stanley Dube, 麻豆原创 head of solution advisory. Standing alongside a robot wearing a tracksuit carrying 麻豆原创鈥檚 AI assistant brand Joule, Dube said: 鈥淭he fear I have had is that AI is going to take my job.鈥�

However, having moved past that fear, he and Joule addressed questions about how organisations can adapt to AI, redesign jobs and processes, maintain governance and build a competitive advantage. In a theoretical example, Dube asked about the specifics of a project.

鈥淚 already know the status,鈥� answered Joule. 鈥淚 also know who is usually responsible for the delays: you, Stanley Dube.鈥�

Debate around AI replacing workers and robots taking control has become familiar, but 麻豆原创鈥檚 demonstration gave Joule a physical presence beyond a computer screen. The robot appeared to serve as a representation of the software assistant rather than a demonstration of autonomous physical AI. Although the presentation carried an element of theatre and Joule鈥檚 responses may have been preprogrammed, the exchange pointed towards a future in which AI agents could take on a more visible and collaborative role in the workplace.

Dube asked Joule: 鈥淲hat do we, as entities and companies, actually have to do to survive and thrive in the age of AI?鈥�

Joule answered: 鈥淢ost organisations do not have an AI problem; they have an adaptability problem. [This is] a massive waste of time and capital. I am built directly into your 麻豆原创 applications. While you slept, I autonomously reconciled 84% of your finance accounts, predicting a pump failure at Secunda to generate a maintenance order and rerouted logistics around a major issue.鈥�

Joule鈥檚 response framed the main obstacle as organisational rather than technological. AI systems may process information and act within seconds, but the benefit can be lost when decisions still depend on lengthy approval chains and slow human processes. In that situation, advanced technology becomes the equivalent of placing a Ferrari engine in a donkey cart: the system has considerable power, but the surrounding organisation cannot move at the same speed.

Dube said employees might find themselves arguing with AI agents in future, but that should not necessarily be a cause for concern.

Joule said: 鈥淩emember, AI is the enabler. Adaptability is the challenge. The future belongs to those who learn how to adapt because of AI, not just those who adopt.鈥�

The presentation extended a strategy outlined at 麻豆原创鈥檚 Sapphire conference in May. As , 麻豆原创 presented the Business AI Platform as an environment for developing and governing agents that work across enterprise operations. The approach uses ERP systems as the source of business data, processes and controls, allowing agents to perform tasks within established organisational boundaries.

Standard Bank provided a practical example of the preparation required to support 麻豆原创鈥檚 vision. The bank has modernised core enterprise systems using 麻豆原创 technology, establishing a platform from which further automation and AI applications could develop.

Vanessa Padiachee, Standard Bank Group CIO for corporate functions, said: 鈥淚f you look at the pace of change, technology is changing rapidly. AI is no longer just around experimentation and production use cases. Organisations are now going beyond that to look at enterprise scaling use cases.鈥�

Padiachee said 麻豆原创 was an important part of Standard Bank鈥檚 broader technology programme. She said organisations must manage rapid technological change while keeping major systems aligned with practical business requirements.

Standard Bank is focused on modernising the systems needed to support future automation and AI deployments rather than describing an autonomous AI implementation.

That work receives far less attention than demonstrations of agents and automated decisions. However, 麻豆原创鈥檚 autonomous-enterprise vision still depends on businesses having systems, processes and employees capable of supporting the technology.

Joule may have stepped beyond the computer screen at 麻豆原创 Connect, but the route towards an autonomous enterprise still runs through the less theatrical work of modernising systems, data and processes.

* Jason Bannier is a data analyst at World Wide Worx and deputy editor of . Follow him on .

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The company outlined its strategy at 麻豆原创 Connect Day 2026, held this week in Kyalami, Johannesburg.

, MD for southern Africa at 麻豆原创, said the company’s role is to support organisations in implementing and scaling agentic AI across end-to-end systems as they transition towards .

Addressing the complexity and cost that continue to challenge organisations migrating systems and platforms, , VP of customer advisory for EMEA at 麻豆原创, said the company’s new agent-led transformation approach could reduce the effort required for multi-year ERP migrations by 35%.

Agentic AI assistants

麻豆原创 has introduced several migration and modernisation AI assistants, including data management, custom code, configuration, test management and change management assistants. According to the company, these are governed by Joule for both developers and consultants and are designed to execute complex business scenarios by reasoning iteratively and interacting with their environment to achieve defined goals.

Nolla cited 麻豆原创 research indicating that the highest-ranked strategy for maximising ROI from AI is aligning initiatives with clear business goals.

麻豆原创 said AI currently supports about 30% of tasks in the average business, with that figure projected to reach 48% within two years.

, head of solution advisory at 麻豆原创, said a major challenge in AI-driven digital transformation is what the company describes as the “enterprise paradox” 鈥� the expectation of instant enterprise AI clashing with the operational reality of complexity, manual processes and human behaviour.

Standard Bank’s transformation journey

, executive group CIO for corporate functions at Standard Bank, outlined the bank’s use of 麻豆原创 technology to address operational challenges, including end-of-life systems, expiring vendor support and the need for a modern cloud ERP platform to support future innovation.

The bank completed a large-scale ERP migration and implementation programme. Modernising core enterprise systems required careful planning, strong governance and close collaboration between business and technology teams. The programme established a platform capable of supporting growth, operational resilience and ongoing innovation.

Padiachee said one of the biggest challenges was the pace of technological change.

“Organisations are required to continuously adapt while maintaining stability across critical business operations. Change management is just as important as the technology implementation itself,” she said.

Modernisation, she added, should improve agility without creating unnecessary disruption to business operations.

She also highlighted the human factor. “It’s really about keeping people calm during turbulence,” she said, adding that AI is fundamentally changing how businesses operate. “The focus should move beyond experimentation towards delivering measurable value.”

According to Padiachee, AI initiatives should align with clear business outcomes rather than be driven by the technology’s popularity.

She said one of the most significant lessons from the transformation programme was the complexity of Unicode conversion.

“In hindsight, this work should have started much earlier in the programme. Unicode conversion proved more complex than anticipated and became a critical dependency for implementation. Investing time in foundational technical readiness significantly reduces downstream project risk.”

Padiachee also stressed the importance of high-quality enterprise data that is accurate, trusted, well-governed and accessible.

She advised organisations planning system and platform migrations, as well as AI integration, to begin with a clearly defined use case, establish strong partnerships and maintain robust governance and guardrails.

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Not so, says , MD: Southern Africa at 麻豆原创.

鈥淓RP is no longer just a system of record,鈥� she tells delegates to 麻豆原创 Connect taking place today in Kyalami.

鈥淲ith agentic AI, we can ensure it runs end-to-end business processes, creating autonomous ERP.鈥�

Today, AI supports 30% of tasks in the average business, according to an Oxford Economics study. And this is projected to rise to 48% in the next two years.

vice-president: customer advisory for EMEA at 麻豆原创, points out that around 40 000 of 麻豆原创鈥檚 customers have already adopted 麻豆原创 Business AI in their productive systems.

鈥淎nd we are learning from that,鈥� he says.

Nolla believes 麻豆原创 is well placed to help customers adopt AI, through its 麻豆原创 Autonomous Enterprise vision.

The key components of this vision are three-fold

鈥淵ou have the capability to bring teams long with one engagement layer 鈥� Joule.

鈥淭eams connect with embedded agents and AI in 麻豆原创 Autonomous Suite, using best practices and processes.

鈥淎nd customers have the ability to extend agents, maintaining context and reasoning, and ensuring governance with .鈥�

Nolla explains that is the engagement layer that connects experts in the business with the AI processes.

It has been available for some time and has been widely used to unify the AI experience. It has also been updated along the way, for instance with Joule Consultants that have more than 100 certifications.

A few weeks ago, 麻豆原创 announced additional evolutions. leveraging Harness-powered Joule and Joule Work to create spaces for specific tasks.

鈥淛oule is the engagement layer to bring the people along,鈥� Nolla summarises.

Adding the processes and best practices, 麻豆原创 Autonomous Suite embeds AI scenarios throughout the portfolio, from HR, customer service, supply chain, finance and industry solutions.

With hundreds of agents available, Joule Assistants help workers by bringing together the relevant agents to perform specific tasks.

鈥淭hink of it as a new team member helping staff accomplish their goals,鈥� Nolla says.

In addition, 麻豆原创 Industry AI is AI that already knows how specific industries operate, so the system can work with context.

鈥淏ut does AI have a true understanding of your business? Is it aligned to your KPIs, and does it have the governance in place?鈥� Nolla asks.

鈥溌槎乖� Business AI Platform brings these capabilities to the business.鈥�

With Joule Studio giving workers the ability to create new agents on the fly, the possibility of hundreds 鈥� even thousands 鈥� of agents within the business could become unwieldly.

鈥淪o governance is more important than ever,鈥� Nolla says. 鈥淭he AI Agent Hub gives IT the ability to connect and understand these agents. They can discover, manage and govern all the agents in one place.

鈥淭his gives the business power, control and trust.鈥�

Within the next few months, 麻豆原创 will also release enriched agentic AI tools and assistants to help with data management, configuration, development and testing to improve migration projects.

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Companies are reviewing their ERP strategies as they balance digital transformation goals with tighter budgets, operational complexity and the need to demonstrate measurable business value, they say.

Andrew Strachan, director of sales at Spinnaker Support Southern Africa,  companies across Africa are reassessing ERP support strategies as decision-makers seek to modernise their environments while managing costs.

“Enterprise software decisions are not like other technology decisions,” said Strachan. 鈥淭imelines are longer, dependencies run deeper and the cost of reversing course 鈥� if reversing course is even possible 鈥� is often measured in years and very substantial sums.”

According to Strachan, the relationship between a major ERP vendor and its customers rests on more than product capability alone. “It is built on trust: trust in the roadmap, trust in the commercial model and trust that the terms you commit to today will not be materially redefined once your business is locked in.”

Gerhard Alberts, head of customer evolution at 麻豆原创 Africa, said trust is ultimately measured by business outcomes.

鈥淲hile customers rightly expect transparency and choice, the greater risk in today’s competitive environment is often the cost of inaction,” he said. “Ultimately, success is measured not by the technology deployed, but by the operational improvements, agility and competitive advantage it enables.鈥�

Alberts said the pace of technological change means companies must adopt relevant technologies to remain competitive, and that customers must be equipped with the most relevant tools to navigate a shifting market. “By not innovating, customers run the risk of attracting direct and potential costs in terms of system and infrastructure stability, security and compliance. This results in an inability to stay competitive across multiple markets due to a lack of agility.鈥�

Strachan said new platforms and regular vendor upgrade announcements are adding pressure on companies already facing constrained budgets, skills shortages, infrastructure complexity and currency pressures.

鈥淚n South Africa and across the African market, large technology decisions are made under intense scrutiny,” he said. “Boards and executive teams are balancing growth ambitions against currency pressure, constrained capital budgets, skills shortages, infrastructure complexity and the need to show clear business value from every major investment. In that context, organisations cannot afford to keep revisiting foundational ERP decisions every few years because the vendor鈥檚 commercial priorities have changed.鈥�

Migration is not modernisation

Courtney Hounsell, client experience manager at Microsoft managed partner Braintree, said AI is reshaping the role of ERP platforms while exposing the limitations of legacy systems. He said outdated ERP infrastructure is hindering AI adoption because many companies mistake cloud migration for digital modernisation.

鈥淢igration is not modernisation,” Hounsell said. “Unfortunately, many companies have merged the two, and the result is a gap that鈥檚 creating incoherence and a lack of visibility, constraining their ability to benefit from AI and its capabilities.”

He explained that cloud migration has been sold as digital modernisation, but this only changes the address of the system. Real modernisation, he said, changes architecture, data models, integration logic and the capacity to generate value. “Companies want their modernisation projects to actively reduce other costs, show long-term ROI and empower their staff with systems that work faster and smarter. So when migration and modernisation are confused, companies end up paying cloud prices for on-premises problems and arrive in the AI era without the foundations required to ensure AI can function effectively.”

Hounsell said the gap between technology investment and business outcomes is widening, leaving companies with limited AI capability and poor data visibility. He cited McKinsey’s “The State of AI in 2025” report, based on a survey of 2 000 executives in 105 countries, which found that 88% of companies have adopted AI in at least one business function.

He said on-premises ERP systems struggle to support AI because data must be extracted, cleaned and transferred before analysis.

鈥淥n-premises ERP systems are struggling uphill within the AI economy,” Hounsell said. “They hold their data in local databases, and to make this usable for AI, it has to be extracted, cleaned and pushed somewhere accessible. Without real-time data pipelines feeding into core systems, AI deployments remain siloed and limited.鈥�

Braintree said ERP modernisation also delivers financial benefits, citing the Forrester Total Economic Impact study of Dynamics 365 Business Central, which found that companies could achieve a 265% ROI, with productivity gains of 12.5% in operations, 15% in sales and 15.6% in finance.

The study also found that companies that modernised successfully avoided more than $30 000 a year in third-party consulting fees, while cloud ERP platforms reduce infrastructure costs and receive automatic updates, including new AI capabilities.

Braintree argued that choosing the right migration partner is as important as selecting the ERP platform itself.

Alberts added that technical debt continues to grow as companies rely on siloed data, ageing infrastructure and extensive custom code, while shortages of legacy skills compound the problem.

鈥淥ver time, doing nothing to save money becomes the most expensive system to maintain, together with the inability to adapt, which has the potential to result in the demise of some organisations,鈥� he said.

Arthur Goldstuck, CEO of World Wide Worx,  after 麻豆原创 Sapphire 2026 that 麻豆原创 CEO Christian Klein described ERP as the “brain” of every business in the age of agentic AI. Goldstuck quoted Klein: 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�

According to Garth Ridgway, senior director for 麻豆原创 at NTT DATA, misconceptions about implementation timelines, affordability and suitability for mid-market companies continue to delay modernisation.

“Many executives still assume ERP transformation requires years of disruption and significant upfront investment,” Ridgway said. “In reality, modern cloud ERP platforms have evolved considerably, enabling organisations to adopt best-practice processes more rapidly, scale according to business needs and realise value far sooner than was historically possible.”

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The next phase of artificial intelligence (AI) should be shaped with Africa, not simply about or for the continent, according to 麻豆原创’s Director of Global Government Affairs and CSR for Africa, .

His comments follow the launch of the , announced yesterday by international leaders to expand access to AI, strengthen trust and increase its social and economic impact.

The commission brings together representatives from governments, businesses and international organisations to identify practical ways to unlock AI’s potential while promoting equitable access to the technology.

Its inaugural meeting will take place during the International Telecommunication Union’s (ITU) AI for Good Global Summit, from 7鈥�10 July in Geneva, Switzerland.

The summit forms part of Digital Week, running from 6鈥�10 July, alongside the first UN-mandated Global Dialogue on AI Governance and the WSIS Forum 2026.

Geness, who will participate in discussions at the summit, said Africa should approach global AI governance with a clear agenda centred on economic growth and inclusion.

“Africa must meet that room with clarity, not caution. Our agenda should be simple and bold: AI governance that expands prosperity.

“That means compute access, skills investment, trusted data systems, open standards, local-language innovation, accountable public procurement, and regulation that protects people without suffocating entrepreneurs.

“It means turning the African Union’s Continental AI Strategy from a document into national roadmaps, investment pipelines and regional co-operation. This is technology diplomacy: 54 nations aligning where they can, rather than negotiating as 54 separate voices. This is where I hope to add value.”

Africa’s representation on the commission has been strengthened by the appointment of Rwandan President Paul Kagame as co-chair alongside Salesforce Chair and CEO Marc Benioff.

According to the ITU, the commission aims to promote equitable access to AI and help narrow the global digital divide.

The organisation said an estimated 2.2 billion people remain offline, leaving around a quarter of the world’s population excluded from AI-driven opportunities.

“A key focus of the AI for Good Global Commission will be to bridge digital divides and help ensure that AI becomes a tool for solving global challenges, not deepening inequalities,” the ITU said.

President Kagame said technology should reduce inequality and broaden access to AI’s benefits.

“One thing is certain: technology is supposed to be a force for good, and we have a responsibility to use it accordingly. Let us work together to reduce inequality and allow more of our citizens to benefit from the good AI can deliver to all of us.”

Benioff said AI’s economic potential depends on maintaining public trust.

The promise of AI is built not only on incredible opportunities for economic growth, but on the foundation of trust required for our shared success.”

ITU Secretary-General Doreen Bogdan-Martin, vice-chair of the commission, said collaboration across sectors would be essential to ensure AI benefits people globally.

“No organisation can single-handedly put AI at the service of all humanity. It will take collective leadership and the combined expertise of partners across sectors to ensure AI benefits everyone, everywhere.”

This article first appeared here:

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, Head of Cloud ERP, 麻豆原创 Business Suite for 麻豆原创 Middle East & South Africa, on why the road to the autonomous enterprise still runs through clean core, trusted data, and the people who must live with the change.

Christian Klein gave Sapphire 2026 its most quotable line when he said no AI agent can compensate for a bad data landscape. For the Middle East and Africa markets that聽Pieter Van Der Merwe聽covers at 麻豆原创, that reads more like a starting gun. Van Der Merwe advises customers across the UAE, a region split between government-mandated agentic AI in the Gulf and parts of Africa still securing their first foundational cloud workloads, yet all staring down the same 2027 ECC deadline.

, he gave a working practitioner鈥檚 view of the market. He was candid about where RISE programs stall, why the first year is organizational change wearing a technology costume, and why prized customizations are often historical workarounds in disguise.

麻豆原创insider: 麻豆原创鈥檚 Africa messaging has intensified throughout 2026, and the autonomous enterprise framing surfaced early from MEA leadership. Is this a pivot, and why does the idea land here first?

Pieter Van Der Merwe: Africa has always been a growth market; what changed is the convergence of cloud ERP, business AI, data sovereignty and skills development. Some African enterprises carry less embedded legacy customization and can move faster. Others run highly customized environments built over years around payroll, procurement, and financial reporting.

The framing of a business that can sense, decide, and act with minimal human intervention resonates here for practical reasons, including resource constraints and the opportunity to leapfrog rather than replicate the mature-market journey. The opportunity is around clean cloud ERP, trusted data and embedded AI as the foundation for more agile, competitive organizations.

麻豆原创i: Africa and the UAE are in very different places. What does a realistic autonomous enterprise roadmap look like for these regions in 2026?

Van Der Merwe:聽It starts with the unglamorous essentials such as modernizing the core and fixing the data foundation. Our CEO, Christian Klein, noted at Sapphire 2026 that no AI agent can compensate for a poor data landscape, so good data is the prerequisite for everything else.

The near-term value lies in the embedded AI scenarios that already live in RISE, such as finance automation, HR workflow and supply chain exception management. These are switched on inside existing 麻豆原创 Cloud environments. The agentic layer arrives as the foundations mature. The African and Middle Eastern organizations well-positioned in 2028 are the ones investing in that foundation now, even when the autonomous vision feels distant.

麻豆原创i:聽When a customer commits to RISE, what do the first 12 months look like, and where does it diverge from expectations?

Van Der Merwe: The first 12 months are a business transformation program disguised as a technology migration. The technology, 麻豆原创 S/4HANA Cloud, infrastructure, and licensing are relatively straightforward. The depth of organizational change, such as how people work, how decisions are made, and how processes are structured, catches organizations off guard. Without governance and stakeholder engagement, even the best platform underdelivers.

The most common divergence is data readiness. Poor-quality, inconsistent master data surfaces early and erodes user trust, which is hard to recover from. The second is customization. Organizations underestimate how much of the current configuration is genuine business logic versus historical workaround, and that distinction is decisive for clean core. One welcome change post-Sapphire is that RISE customers get three Joule Assistants activated in their first year, giving a tangible AI experience during the foundational phase.

麻豆原创i: Post-Sapphire, are customers feeling more urgency on the 2027 ECC deadline, or using the AI vision as a reason to pause?

Van Der Merwe: The 2027 deadline is real. 麻豆原创 has made it clear that ECC customers who commit to migrating most of their landscape to 麻豆原创 Cloud ERP gain access to select AI scenarios in the interim, so there is a bridge. The best-placed customers when agentic capabilities mature are those already running clean-core 麻豆原创 S/4HANA, because that is the foundation the autonomous suite is built on. Waiting for the full vision before starting the foundation is the wrong sequence. If anything, the bigger risk is reorganizing priorities too ambitiously and trying to tackle everything at once.

麻豆原创i: Clean core is the prerequisite for everything 麻豆原创 promises, but in heavily customized landscapes, it can feel like undoing years of work. How do you win a buy-in?

Van Der Merwe: By reframing what those customizations represent. Some encode genuine differentiation, process logic that reflects how the business truly operates, and deserve to be preserved as extensions on  using clean-core methodology. But much of the customization in mature landscapes is a historical workaround, through integration patches and decisions made under time pressure decades ago.

The conversation must involve finance, operations, and process owners. The framing that works is forward-looking: what does clean core unlock, specifically the AI scenarios now in RISE, and what does it cost to keep maintaining the current complexity? As support deadlines approach, that calculation changes sharply. The people dimension matters too. Teams whose identity is built around managing customized systems need a new value proposition of supervising AI-augmented processes rather than wrestling with complexity.

麻豆原创i: The autonomous vision depends on trusted data and standardized processes. How prepared are organizations, and are some underestimating the foundational work?

Van Der Merwe: Both are genuinely hard, and neither is solved at contract signing. Data readiness is the most underestimated challenge. 麻豆原创鈥檚 platform response- 麻豆原创 Business Data Cloud (BDC), Knowledge Graph and the Reltio acquisition- is meaningful, but zero-copy sharing and semantic enrichment do not substitute for master data governance.

Process standardization is the other half. The autonomous suite is built around standardized, cloud-aligned processes, so organizations that customized for years face a real renegotiation. The most forward-thinking organizations treat it as an opportunity to redesign processes for the AI era, rather than replicate old ones in a new system.

麻豆原创i: Where do RISE programs most commonly stall, and what separates the customers who push through?

Van Der Merwe: The stall points cluster in three areas: data-readiness failures that force unplanned remediation; change-management breakdowns where the business disengages and IT drives alone; and integration complexity across mixed 麻豆原创 and non-麻豆原创 landscapes. Those who push through have the qualities of change leadership, such as engaged executive sponsorship, quick decision-making governance, and a willingness to standardize where standardization is available. The technology is mature and stable; the implementation process and organizational alignment are where programs succeed or fail.

麻豆原创i: Joule was positioned at Sapphire as 麻豆原创鈥檚 new front door. What does it mean for a customer mid-journey on RISE?

Van Der Merwe: Customers should be thinking about Joule now, even if full deployment is progressive. The positioning of Joule Work is a significant UX shift. For customers mid-journey, the practical question is which Joule capabilities are already available in their current RISE configuration and whether they are activating them, because the embedded scenarios and early assistant capabilities do not require a completed transformation. The broader Joule Work experience, across web, desktop, mobile and voice, moves to general availability in H2 2026. That timeline is closer than many realize.

麻豆原创i: 麻豆原创 has more than 295 AI-powered scenarios embedded across its applications. Which are getting real traction, and which are still promising on paper?

Van Der Merwe: The strongest traction is where AI is embedded directly into existing workflows, and the value is obvious: finance, HR, procurement, supply chain, and customer service, because they involve high-volume processes and measurable outcomes. Think faster financial close, guided buying and invoice processing in procurement, demand sensing and exception management in supply chain.

Where a use case stays more promising than practical, the problem lies with the customer environment. If data is fragmented, processes are inconsistent, or governance is immature, even strong AI struggles to deliver value at scale.

麻豆原创i: The autonomous enterprise means AI executing actions humans perform today. How are the most forward-thinking customers approaching the human side?

Van Der Merwe: Organizations must treat AI as a work redesign strategy, not a replacement strategy. Employees move from repetitive execution toward supervision, exception handling, judgment, and continuous improvement. People must understand why the organization is changing and what skills keep them valuable, or AI copilots become another layer nobody trusts or uses.

It also demands reskilling, like learning to work with AI, interpreting its recommendations, and escalating exceptions where accountability still rests with people. The most mature organizations build cross-functional teams across business, technology, operations, compliance and change. The principle is simple: autonomous does not mean human-free. It means people focus on higher-value work while intelligent systems handle the repetitive and predictable.

麻豆原创i: Have you seen the RISE-to-autonomous journey deliver something genuinely different from previous 麻豆原创 transformation cycles?

Van Der Merwe: The example of IBM migrating from 麻豆原创 ECC to 麻豆原创 Cloud ERP Private across 175 countries and more than 150,000 users in 18 months is instructive. The move contributed to over $4.5 billion in productivity savings. What is different in this cycle is the speed and scope. A transformation at that scale would once have taken far longer, and the AI tooling now applied to the migration itself, reducing effort by up to 35% on 麻豆原创鈥檚 own figures, is part of that story.

In advanced deployments, the qualitative shift is from static reporting to active intervention. What feels genuinely new is the convergence of data, AI and process in a single governed environment, delivering systems that learn and adapt in real time.

麻豆原创i: What is the one piece of advice you would give to a CIO or IT director in the Middle East and Africa navigating the 2027 deadline and autonomous vision?

Van Der Merwe: Do not treat these as separate issues. The 2027 deadline, the move to cloud ERP, and the autonomous enterprise are the same strategic decision: How ready your organization is for the next decade. The immediate priority is to modernize the core and fix the data foundation, because without it, AI stays trapped in isolated use cases. Then focus on business value: the processes where AI can protect revenue, improve cash flow, reduce risk, or unlock capacity. Do not modernize for technology鈥檚 sake.

Finally, bring people in early. This is as much a leadership, skills, and operating model shift as a technology one. My strongest advice is simple. Start now, start with the core, and build a roadmap that integrates migration, data, AI, and people into a single transformation agenda.

The post 鈥淎utonomous Does Not Mean Human-Free.鈥� Inside the RISE Roadmap for the Middle East and Africa appeared first on 麻豆原创 Africa News Center.