The good news, says , Managing Director: Southern Africa at SAP, is that real-world AI value is already becoming clear. 鈥淎cross critical business functions like finance, HR, procurement, sales and service, and marketing, embedded AI is driving efficiency, accuracy, and smarter decisions at scale. From automating repetitive processes to delivering real-time insights and predictive recommendations, South African companies are unlocking unprecedented gains in productivity and efficiency.鈥�

Analysts suggest African countries could unlock as much as $100-billion in economic value per year听, while a PwC study estimates听听if Africa can claim a 10% share of the global AI market.

鈥淭o unlock this vast economic potential, organisations must integrate AI into core business processes and achieve measurable outcomes for clear use cases. A clean core strategy further allows businesses to respond faster to market changes and adopt new technologies like AI and advanced analytics more easily, creating clear pathways to significant ROI and business impact.鈥�

Of critical importance too is defining and implementing a comprehensive AI framework that prioritises governance at the outset. 鈥淎n effective framework should include a clear AI vision, business-aligned goals, an operating model, and, critically, establishment of AI governance to ensure ethical, secure, and compliant scaling of AI across the organisation.鈥�

Pillay highlights high-impact use cases across five key business functions that South African organisations can implement to boost productivity and drive growth.

1 Smarter financial insights & automation听

Finance departments are under increasing pressure to speed up reporting cycles, reduce operational costs, and strengthen cash flow visibility. 鈥淚n South Africa, financial institutions are leveraging AI for everything from fraud detection to multilingual support, but practical automation is where the biggest gains are currently being made,鈥� says Pillay.

Automated receivables matching is one such win. By applying machine learning to past payment behaviours, companies can automatically match and clear bank statement items,听听and accelerating payment cycles.

Another high-impact tool is AI-assisted cost centre analysis. 鈥淚nstead of manually wading through complex reports, finance teams can use generative AI to instantly summarise data, highlight KPIs, and recommend next steps,听听and freeing up analysts to focus on strategic insights,鈥� says Pillay.

2 Smarter hiring and better talent fit

AI is transforming HR from a reactive cost centre into a strategic function. Nearly 70% of South African HR teams听听to streamline recruitment, performance reviews, and workforce planning, delivering up to 35% process efficiency gains.

鈥淥ne practical use case gaining widespread adoption is AI-powered applicant screening, where machine learning scans CVs to match applicant skills with job requirements. This听听and speeds up hiring for hard-to-fill roles.鈥�

Pillay points to AI-generated job descriptions as another time-saving tool. 鈥淗R professionals input a few keywords and receive polished, bias-reducing job listings in seconds, helping improve candidate fit and听.鈥�

3 Scaling service and sales excellence

South African telecoms, ecommerce platforms and financial institutions are seeing measurable gains from AI-powered customer service.

鈥淭ools like chatbots and virtual assistants now handle routine queries with 24/7 availability, cutting service costs and improving customer satisfaction,鈥� explains Pillay. 鈥淲here a human touch is still needed, AI is helping agents generate case summaries, allowing them to respond faster by compiling email threads and communications into a single, easy-to-read brief. This can听听and improve first-contact resolution by 10%.鈥�

In field service, AI-driven equipment insights give technicians a clear picture of past service activity, parts used, and common failure patterns, resulting in 65% higher productivity and a 5% bump in first-time fix rates,听.

4 Streamlined sourcing and planning

Procurement teams face mounting complexity as they juggle supply risk, regulatory compliance, and shifting market dynamics. According to Pillay, AI is easing this burden by automating strategic sourcing tasks and offering real-time decision support.

鈥淎I tools have become indispensable to category planning efforts,听. This is helping managers move 90% faster and make more informed and proactive decisions.鈥�

Another valuable application is automated statement-of-work (SOW) generation. With minimal inputs,听, slashing processing time by 71% and improving project alignment by providing clearer briefs to suppliers.

5 Improved customer engagement and inventory management

AI鈥檚 value in marketing is growing fast, especially in segmenting audiences and triggering personalised campaigns. South African firms are tapping into predictive tools to boost engagement and pre-empt churn.

鈥淲ith AI-powered audience segmentation, marketers can automatically group customers based on predicted behaviours such as likelihood to convert or churn, driving higher rates of engagement and more relevant, timely outreach,鈥� says Pillay.

In back-office support, AI-generated sales orders now听, cutting manual effort, speeding up processing, and reducing errors by 25%.

鈥淎s embedded AI matures and business systems become more intelligent, these use cases will continue to expand, driving a new era of productivity, insight, and competitive advantage across every function,鈥� says Pillay.

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As generative AI adoption accelerates and the pursuit of artificial general intelligence gains momentum, key African markets are facing a widening AI skills gap despite universal recognition of their importance.

New research reveals that 61% of mid-size and enterprise-level companies in Kenya, Nigeria, and South Africa consider AI skills to be 鈥榚xtremely important鈥�, while another 38% regard them as 鈥榲ery important鈥�. Together, this reflects a near-unanimous 99% consensus that AI skills are critical to business success.

This is unveiled in听Africa鈥檚 AI Skills Readiness Revealed, a report commissioned by 51风流and conducted at the end of 2024. The findings provide insights into how African companies are transforming their skills development efforts to meet the demands of the age of AI.

鈥淭he business impact of a lack of AI skills availability is already evident, with 90% of companies in our research citing negative impacts that include project delays, failed innovation initiatives, and an inability to take on new work,鈥� said Nazia Pillay, interim MD for SA at SAP, during a media briefing last week. 鈥淭his year鈥檚 data shows the pervasive need for AI skills across African organisations, and the negative impact, both on performance, competitiveness and innovation when organisations lack these skills.

鈥淥ur first report was conducted just as we exited the worst of the pandemic impact. At the time, companies were facing several challenges with attracting, retaining and upskilling suitable qualified tech workers, especially in the wake of the rise of remote and hybrid work environments. This year, the business landscape has been transformed by the impact of AI technologies and the search for relevant skills.鈥�

The research uncovered two key findings that received unanimous agreement. All respondents expect demand for AI skills to increase in 2025, with nearly half anticipating a 鈥榮ignificant鈥� rise. This anticipated surge in demand highlights the urgency for businesses to strengthen their AI capabilities to remain competitive.

In addition, all companies foresee some level of AI-related skills gap this year, underscoring the urgency of developing and retaining AI talent. The widespread expectation of a skills gap suggests that organisations are bracing for challenges in accessing the expertise needed to implement AI-driven projects effectively.

鈥淪kills related to AI are hugely in-demand among African organisations, with 85% saying AI development skills are a priority, and 83% prioritising generative AI skills,鈥� said Pillay. 鈥淭o help close the AI skills gap, two-thirds of organisations are introducing career development initiatives with AI specialisation to upskill or reskill employees.鈥�

To close the gap, companies are adopting a range of strategies beyond career development programmes. These include automating IT processes (66%), upskilling existing employees (58%), recruiting new talent with AI expertise (52%), and bringing in external specialists (45%).

The most in-demand tech skill among African organisations is cybersecurity, with 86% of companies identifying it as important 鈥� up from 63% in the previous research. Pillay said this rise is likely driven by the rapid growth of Africa鈥檚 digital economy and the increasing number of citizens entering the digital space through public and private sector initiatives.

Training, skills development in the spotlight

Pillay said companies are stepping up their IT training and skills development efforts to help meet the demand for skills. Additionally, the portion of companies鈥� IT or HR budgets allocated to skills-related initiatives has declined since 2023.

鈥淣inety-four percent of African organisations offer training and skills development to employees at least monthly, an increase from 74% in our last survey. The number of companies offering training opportunities to employees at any time also increased from 28% in our last survey to 37% this year.

鈥淭he drop in budget allocation for skills development requires an urgent rethink. Organisations that don鈥檛 invest in appropriate skills now may find they are unable to leverage new innovations and emerging technologies, leaving them trailing their more skills-enable competitors.鈥�

Pillay said that rescaling and upscaling is considered one of the top skills-related challenges for all African organisations this year. The findings reveal that 37% of organisations make training available to their employees at any time, and 98% of organisations see AI training as top priority.

These findings suggest that while organisations are expanding access to training, they may not be backing this up with sufficient investment. The disconnect between growing training efforts and shrinking budgets points to a need for more strategic allocation of resources. Without sustained financial commitment, companies risk falling short in equipping their workforce with the skills required to remain competitive in an AI-driven economy.

Changing workplace expectations

Workplace expectations are shifting rapidly as organisations adapt to new technologies and changing employee priorities. In addition to technical expertise, companies are placing greater emphasis on non-technical attributes such as adaptability and affordability. These changes are driven in part by the growing need to upskill and reskill employees for roles shaped by artificial intelligence, as well as by evolving preferences around hybrid and remote work.

鈥�80% of organisations said that enabling hybrid and remote work is their biggest tech related skills challenge 鈥� up from 32% in our last survey,鈥� said Pillay. 鈥淣ow, 58% of organisations offer fully remote options, and 56% of organisations have a hybrid option which they use to attract and retain top talent. When you look at employees, 83% of employees globally consider hybrid working to be an ideal environment.

鈥淚n 2023, technical skills and industry-specific skills were the top attributes. Affordability was somewhere near the bottom, with less than a third of organisations saying they consider it during the hiring process. This year, affordability is the number one candidate attribute for African organisations, with adaptability a close second.

鈥淩eskilling is a top skills-related priority for 38% of companies this year, with 48% saying the same of upskilling employees. Unsurprisingly, two-thirds of companies said helping employees understand why reskilling is necessary is one of the top challenges this year.鈥�

* Read SAP鈥檚 鈥楢frica鈥檚 AI Skills Readiness Revealed鈥� report听.

*Jason Bannier is a data analyst at World Wide Worx and writer for听. Follow him on听.

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Joule, SAP鈥檚 AI business assistant, has been enhanced with new features, including collaborative AI agents that expand the platform鈥檚 capabilities.

Announced during the online 51风流TechEd 2024 conference yesterday, these agents are designed to support 80% of SAP鈥檚 most-used business tasks. They embed Joule more deeply across SAP鈥檚 portfolio and enhancing productivity by breaking down silos, said the software maker.

鈥淪AP鈥檚 innovation drives real business outcomes, and today鈥檚 advancements help customers harness the power of AI, data, and new development solutions to catalyse growth,鈥� said Muhammad Alam, member of the 51风流executive board.

鈥淒rawing on SAP鈥檚 unmatched business and technology expertise, the AI innovations we鈥檙e announcing at TechEd forge a new human-AI partnership to transform the landscape of modern business.鈥�

Joule Studio, a development tool that allows users to build and customise applications using Joule鈥檚 AI capabilities, is now integrated into 51风流Build. A low-code app development platform, Build enables both business users and developers to create and deploy custom Joule skills.

Michael Ameling, EVP and chief product officer of 51风流said: 鈥淲e are making Joule even more flexible and useful with Joule Studio in 51风流Build. It allows partners and customers to create and deploy custom Joule skills.鈥�

Joule has also expanded to include collaborative AI agents that autonomously handle intricate business workflows, adapting their strategies to meet shared objectives. These multi-agent systems tackle specific tasks, allowing them to work together on complex business processes.

鈥淛oule now goes Agentic,鈥� said Ameling. 鈥淪pecialised AI agents work autonomously together to solve complex problems.鈥�

New improvements to the ABAP (Advanced Business Application Programming) large language model (LLM) were introduced. This LLM, trained on over 250-million lines of 51风流S/4HANA Cloud code, is now integrated into the open-source Eclipse framework, providing ABAP developers with enhanced tools for development. Currently available to select customers and partners in an early adopter version, the ABAP LLM is expected to be generally available in the first quarter of 2025.

51风流Build is launching new AI-driven features like code explanation and documentation search, aimed at reducing development time for Java and JavaScript developers. The platform鈥檚 Extensibility Wizard will let developers access 51风流Build directly from 51风流S/4HANA Cloud Public Edition, simplifying the process of extending 51风流solutions.

Two real-world use cases were highlighted during the event:

1. Dispute management: Autonomous AI agents analyse and resolve disputes related to invoices, unapplied credits, and denied payments.
2. Financial accounting: AI agents automate key financial tasks such as bill payments and ledger updates while quickly addressing inconsistencies.

51风流Knowledge Graph

51风流also unveiled the 51风流Knowledge Graph, a solution designed to unlock more value of 51风流data by connecting it with rich business context. Accessible through 51风流Datasphere and Joule in early 2025, it will help users map relationships across SAP鈥檚 vast data landscape, empowering better decision-making.

鈥淏y combining the knowledge graph engine with the vector engine, you can harness the power of structured and unstructured data,鈥� said Ameling. 鈥淭his is enabled through a triple store implementation graph data processing and analytical capabilities via SPAR-QL. As such, the knowledge graph engine can also enhance work scenarios and make them even more precise and relevant.鈥�

* Visit the 51风流website听.

* Jason Bannier is a data analyst at World Wide Worx and writer for听. Follow him on听听补苍诲听听at @jas2bann.

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While there is apprehension regarding job displacement, income reductions from shortened work hours, and the threat of identity theft, the narrative is far from gloomy. The advent of AI is not a harbinger of joblessness but a beacon for the creation of novel employment opportunities, necessitating a pivot towards embracing and integrating AI into the workforce.

The potential is limitless, particularly in developing economies such as ours. By leveraging AI tools for data analysis, farmers can gain insights into crop health, soil conditions, and weather patterns, leading to more informed decisions and higher yields with lower resource inputs. In areas where healthcare infrastructure is underdeveloped and there is a scarcity of medical professionals, AI can significantly improve access to quality healthcare services.

AI-driven diagnostic tools, telemedicine platforms, and health monitoring apps can extend healthcare services to remote areas, reducing the need for patients to travel long distances for basic healthcare.

Many developing economies suffer from low levels of banking penetration and financial inclusion. AI has the capacity to change this through fintech innovations. By utilising AI and machine learning algorithms, fintech companies can offer personalised financial products, improve credit scoring methods, and extend banking services to previously unbanked populations through mobile platforms.

But there is an important caveat. Paul Daugherty, chief technology officer of Accenture, encapsulates this transition best, advising to 鈥渋nvest more in the people than in the technology鈥�. This principle underscores the importance of human capital in the age of AI, advocating for a workforce that is not only technologically proficient but also adaptable and innovative.

Generative AI, a focal point of Accenture鈥檚 Tech Vision 2024, exemplifies the symbiotic relationship between human ingenuity and artificial intelligence. It is set to redefine the essence of work, transforming roles into that of advisors, creators, developers, and protectors within the enterprise sphere. For example, Accenture鈥檚 initiative to automate 51风流documentation exemplifies how AI can streamline productivity and tackle complex challenges, highlighting a shift towards more engaging and meaningful work.

The transformation does not stop at job enhancement; it extends to the genesis of new career paths. As generative AI permeates various sectors, there is a burgeoning demand for roles that blend technical savvy with creative and strategic thinking. This shift is catalysing a comprehensive re-skilling movement, spearheaded by organisations keen on nurturing a workforce that is resilient and future ready.

Amid these technological strides, the essence of human-AI collaboration becomes ever more pronounced. AI technologies, including semantic search engines, transformer models, and large language models, are revolutionising how we interact with digital systems, making these interactions more intuitive and contextually rich.

This is not just a leap in technology but a paradigm shift in human-computer interaction, fostering a more integrated and seamless blend of digital and human intelligence.

However, the journey towards a harmonious human-AI coexistence is paved with ethical considerations. Privacy, transparency, and inclusivity stand at the forefront of this venture, ensuring that AI development is aligned with societal values and norms. It is about crafting AI systems that are not just intelligent but also ethical and human-centric, reflecting our collective aspirations for a future where technology amplifies human potential.

In South Africa, this evolution presents a unique set of challenges and opportunities. The key to navigating this landscape lies in fostering a culture of continuous learning, ethical inquiry, and inclusive design. By doing so, we can ensure that the benefits of AI are universally accessible, bridging the gap between technology and humanity.

So, what types of job am I talking about? Consider the following skills to which local companies need to start applying their minds.

As AI systems become more integrated into daily life and business operations, there is a growing need to ensure these technologies are developed and deployed responsibly. An AI Ethics Officer is responsible for creating guidelines that govern the ethical use of AI within organisations.

AI in healthcare is not just about data analysis; it is also transforming patient care through AI-enhanced medical devices and personalised medicine. AI-enhanced Healthcare Technicians specialise in operating, maintaining, and interpreting data from AI-powered medical equipment, such as diagnostic imaging machines and robotic surgical systems.

The accuracy of AI models depends heavily on the quality of the data on which they are trained.

Data annotation specialists play a crucial role in the AI development process by labelling data accurately, which is then used to train machine learning models. This can involve anything from identifying objects in images for computer vision tasks to annotating speech for natural language processing systems.

Integrating AI into existing business processes requires not just technical knowledge but also a strategic vision. AI business integration specialists work at the intersection of AI technology and business strategy, helping organisations identify opportunities for AI implementation that align with business objectives.

With the rise of chatbots and virtual assistants, there is a growing need for professionals who can design AI-powered conversational interfaces that provide a seamless and engaging user experience. Conversational AI designers combine expertise in AI, linguistics, and user experience design to create systems that can understand and respond to human language in a natural and intuitive way.

The focus must now shift from merely adapting to AI to actively shaping its trajectory in a manner that enriches human society. It is a call to action for all stakeholders 鈥� businesses, educators, policymakers, and individuals 鈥� to embrace this era of human-AI collaboration with optimism and a shared commitment to a future where technology and humanity coalesce to unlock unprecedented possibilities.

Ntsako Baloyi is a senior manager within the technology business at Accenture, Africa

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However, while everyone agrees the technology is a game-changer for business, the question being asked more and more in the boardroom is whether AI is truly ‘enterprise-grade’.

Business AI is not new

While hype about AI has reached unprecedented levels, the technology itself is not entirely new.

Nick Bostrom, in his book 鈥淪uperintelligence鈥�*, first published over ten years ago, provides an excellent summary of the progression of AI technology. This contemporary work captures the stages of AI – the inflated expectations; the plateauing; and the breakthroughs.

Enterprises have long relied on machine learning to power advanced analytics and predictive capabilities in a broad range of use cases – from manufacturing to finance operations to procurement and supply chain. These algorithms have equipped business leaders with information to drive greater operational efficiency.

AI has also been used extensively in traditional forms of algorithms, for example search engines, which defined an entire era of our technological development and transformed entire sectors, most notably the advertising industry.

Mounting issues with AI’s enterprise readiness

But what works on the web does not necessarily work in business. The Internet doesn’t care about authorisations. The C-suite does.

As concerns over privacy and data protection mount – especially in light of ongoing regulatory pressures – many companies have implemented restrictions over the use of open GenAI tools.

This is for good reason. Imagine an employee shares financial statements, vendor contracts or salary information with a GenAI tool that then reuses that information in answering prompts from other users.

A GenAI tool without an authorisation element is simply not enterprise-grade, and probably doomed to be confined to a single use case or department, limiting its ability to deliver value to the broader business.

Security issues also arise with the concept of data lakes, which combine enterprise and external data sources for AI purposes. Data lakes can be treacherous to enterprises, especially when data must be exported outside of large enterprise applications.

Here, a federated approach that leaves enterprise data at their origin and does not copy or transfer data is needed. Critically, organisations must maintain the semantic layer of the data, which can be the Achilles heel of every data lake project and, consequently, the GenAI models trained on that data.

Beware of hallucinations

However, the greatest danger in AI that is not enterprise-grade lies in its tendency to hallucinate.

Gen AI is an excellent algorithm that fundamentally learns by looking at what is available within its domain, usually the internet. Let鈥檚 be honest 鈥� you can鈥檛 trust every piece of information found on the internet anymore.

In an enterprise environment, CEOs are seeking the 鈥榮ingle version of truth鈥�. That means fact checking is important but begs the question: 鈥渨hich is the dataset on which I should train my Gen AI?鈥�. The simple truth is that business leaders cannot build products or develop innovations using models that make things up or use insights based off false or inaccurate information.

Here, application suite vendors have the upper hand. The business applications that power the world’s enterprises have a wealth of business data that can be mined by AI algorithms to produce accurate, relevant, and reliable insights. Vendors in this space also have significant expertise in business processes and contextualised data – the perfect sources for training effective GenAI.

There’s no doubt that enterprises will benefit from the power of AI in the coming years. Whether it is enterprise-ready comes down to individual systems and tools. While some already have enterprise-level capabilities, others may not yet meet all the requirements for reliability and security. 听Business leaders must take care to build out AI use cases that can deliver value to the business, rely on robust datasets, and live up to expectations. These guardrails will ensure business AI solutions that are relevant, reliable, and responsible.

*Superintelligence – Paths, Dangers, Strategies was written by author, Nick Bostrom, and first published in 2013 by Oxford University Press

听

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As organisations increasingly embrace generative AI to derive insights, automate processes, and drive innovation, the foundation of accurate and well-organised data within their business systems becomes pivotal for realising the full potential of AI applications.

The IDC forecasts that , growing at a CAGR of more than 73%. Much of the spend will be directed to GenAI business cases where productivity boosts are paramount. found that GenAI could add the equivalent of $2.6-trillion to $4.4-trillion in productivity gains annually.

However, much of this latent potential will remain untapped unless organisations can safeguard their AI investments with accurate, dependable data. There is an indispensable connection between the correct data setup in enterprise systems and the success of generative Artificial Intelligence (AI).

Companies seeking to leverage AI as a long-term value driver must therefore ensure they maintain trust and integrity in the data powering their algorithms.

Trust drives AI value

Trust is a critical component of responsible AI adoption. By utilising reliable data, organisations can build and maintain trust with users and stakeholders, fostering a positive relationship between AI technology and society.

Trust is also important for accurate real-time decision making. In today鈥檚 dynamic and fast-paced business landscape, organisations and leaders need to make informed decisions based on accurate data-driven insights. By aligning the outcomes of analytics processes with their own strategic objectives, business leaders are better able to take optimal action and steer the company through adversity, or take advantage of emerging opportunities.

It is therefore important that the data is indeed reliable to prevent erroneous outputs which could be costly and negatively impact an organisation and its reputation. When users trust the output of generative AI applications, the business benefits from higher levels of collaboration and innovation.

To build trust and mitigate risks associated with AI adoption, companies need dependable data that holds the necessary insights and avoids bias. This increases the likelihood that businesses and end-users take the calculated risks necessary for broader AI deployment.

Advantages of data-driven business strategies

To drive greater adoption of AI solutions, organisations must continuously improve their data strategies. This provides several advantages to the success of the business, including:

Greater competitiveness: Organisations with a good data strategy gain a competitive edge when their high-quality data is partnered with powerful AI algorithms to produce better strategic choices and business outcomes.

Increased operational efficiency: Well-managed and high-quality data promotes streamlined business processes. When data is accurate and readily available, operations can more easily be optimised, resulting in cost efficiencies .

Improved innovation and scalability: By leveraging insights built on a good data strategy, businesses can identify market gaps, explore new opportunities, and create products or services that meet evolving customer needs faster than their competitors.

Organisations must also not underestimate the impact of transformative data innovations that help them harness the full power of their data to drive deeper insights, faster growth and more efficiency in the era of AI. The introduction of new data innovations enable organisations to deliver meaningful data to every data consumer with business context and logic intact – enabling them to adapt faster to market changes and make more efficient decisions. The newly-launched 51风流Datasphere solutions, for example, mobilise an extensive global partner ecosystem to enable organisations to transform their business data fabric architecture, allowing them to access insights from their data wherever it resides.

Key elements of an AI-ready data strategy

Organisations that consistently unlock business value from their data-driven strategies have a few characteristics in common. The key elements to enhancing data strategies for AI readiness include:

Strong alignment with business objectives: A well-defined data strategy aligns with the overall goals and objectives of the organisation by establishing a clear roadmap for leveraging data to meet business requirements and objectives.

Effective data governance: Establishing data governance frameworks within the data strategy ensures that data is treated as a valuable asset. Clear ownership, accountability, and data stewardship protocols lay the foundation for maintaining data integrity and consistency.

The highest levels of data quality: The accuracy and reliability of digital transformation and related AI implementations hinge on the quality of the data being input into the system. Incorrect or inconsistent data at the outset can lead to errors and inefficiencies, extending project timelines and adding layers of additional costs and complexity.

The use of industry best practices: Following industry best practices for data setup ensures compatibility and optimal utilisation of the modules being implemented at lower cost and with less complexity. Adhering to recommended data structures, field configurations, and master data management principles is essential for a seamless project in support of AI readiness.

A careful and considered data migration: Proper data setup involves meticulous planning for data migration from legacy systems to the new system. This includes data cleansing, transformation, and validation processes to ensure a smooth transition without compromising data integrity.

Achieving AI readiness demands a holistic approach to data setup, data strategy, and governance. Organisations that prioritise these guidelines will be better positioned to unlock the full potential of AI, foster innovation, and maintain the highest ethical standards.

By adhering to these principles, businesses can navigate the complexities of AI deployment responsibly and contribute positively to societal and economic advancements.

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The global economy continues to be in a state of flux as geopolitical conflict, supply chain pressures, inflation, technology-led disruption and changing consumer needs put pressure on companies and decision-makers.

From the desperate need for more sustainable alternatives to the way we do business to the incomparable impact of AI on every facet of our personal and professional lives, business leaders face a challenging time ahead. By taking stock of emerging trends, however, business leaders may be better able to ride the waves of change and steer their companies through turbulent waters.

These are the key trends that African enterprises should take heed of in 2024:

Trend 1: AI adoption becomes grounded in business value

Generative AI received an astonishing amount of hype in 2023, and was a bolt of lightning that made every business and technology leader sit up and take notice. Today, it’s not a matter of if businesses will adopt AI, but rather how quickly they can deploy and enjoy AI-driven benefits.

In 2024, business leaders will look beyond the hype and seek AI solutions that deliver real-life use cases and benefits. At an operational level, organisations may quickly realise that the quality of their AI outcomes depend largely on the quality of their data.

Technology providers such as 51风流will be indispensable in this conversation, thanks to the huge volumes of data and transactions running through their systems and broader business network. Business leaders will leverage the tech providers’ expertise to access the data they need, visualise it, and take decisive actions to drive successful outcomes.

Trend 2: Sustainability takes centre stage

As the world continues to warm and the consequences of climate change hit home for billions of people, sustainability will take centre stage in the business and technology world.

In 2024, the energy industry will shed its view of the customer as simply a commodity user in favour of the prosumer model. Industry leaders will aim to not only secure loyalty and create retail-like experiences, but encourage users to make active contributions to the stability and health of the grid.

This may involve keeping customers informed of how they can make the best, most sustainable decisions over energy use, or see consumers feed excess energy – for example from rooftop solar – into the grid to stabilise supply and contribute clean energy.

In addition, mounting pressure from regulators, consumers and investors will see organisations build more sustainable supple chains with lower carbon emissions and greater use of circular economy principles. This will require extensive innovation in data and analytics to provide business leaders with end-to-end visibility over their environmental impact across the broader supply chain.

Those companies that do succeed in leveraging technology to build truly eco-conscious supply chains will not only unlock new sources of innovation and revenue, but secure long-term profitability for years to come.

Trend 3: Procurement advances are powered by User Experience

In the rush for digitalisation, enterprises will continue to enhance their procurement processes, driving the need for more intuitive user interfaces. Procurement is evolving from a tactical to a strategic function to drive greater value throughout the organisation.

AI and analytics will be deployed to support procurement professionals as they seek ways to spend more time on value-adding tasks. In 2024, the demand for technologies that enable value-based procurement will increase, enhancing the organisation’s ability to leverage procurement to deliver value in other parts of the business, such as sustainability.

Trend 4: Supply chains become more resilient

Global supply chains are still under severe pressure, thanks to a combination of geopolitical disruption, inflation, environmental factors and the ongoing ripple effects of the pandemic. In 2024, expect a surge in supply chain technology investments as organisations seek greater visibility, agility and risk resilience.

In particular, AI holds huge promise for its ability to enhance organisations’ ability to sense, recognise and react to disruptions and opportunities in new and exciting ways. The key to unlocking AI’s benefits hinges on connected data and collaboration throughout the organisation.

Business leaders must lead the charge by ensuring AI is integrated with every layer of the supply chain network to achieve measurable business outcomes. This will unleash a new era of hyper-predictive and efficient logistics, revolutionising the way goods flow from factory floor to consumers.

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The focus of more than 5,000 tech and business decision-makers was fixed firmly on AI and what it could do for their businesses, right now 鈥� the products 51风流has released through 2024, and what is coming next.

With responsible, reliable, and relevant AI that鈥檚 built for business, the view of the thousands of delegates at TechEd 2023 was that the future is looking bright.

There was a wealth of incredible insight and opportunity at TechEd. In fact, it was a little bit like going back to school because the things that stood out to me were the ABCs.

A is for Automation

First, I was struck by the enormous potential businesses can realise through the power of enterprise automation.

With the help of AI, technology is helping developers and IT teams automate repetitive, mundane tasks and make better decisions, faster. By embedding generative AI capabilities into , , and , we鈥檙e helping customers analyse, integrate, automate, and monitor business processes way more simply 鈥� and then immediately write the code to make those processes better. It鈥檚 that easy.

In my discussions with customers, it was clear that complementing process improvement and insights with enterprise architecture insights will be a real force for change in the future. Customers are excited to understand how to optimise and tune their architecture for the best performance across their entire IT stack.

But this isn鈥檛 future-gazing. Businesses are seeing real results today. Take , one of Asia鈥檚 leading healthcare companies, providing pharmaceutical distribution and digital and commercial services across 26,000 direct outlets. Zuellig Pharma implemented best-in-class processes across its 51风流infrastructure, creating more than 180 automations using 51风流Build Process Automation to streamline and simplify its business.

B is for Build

听Aligned to the focus on automation is the empowerment of a new, powerful resource for IT departments 鈥� citizen developers enabled by . And given every developer will be an AI developer, the opportunity for an AI-infused future is tantalising.

, CIO of Indian car giant , said it best.

鈥淲e started identifying tasks that don鈥檛 require a lot of human intelligence and that enabled our human workforce to focus on more strategic initiatives,鈥� she said. 鈥淭hat led us to automate more than 250 business processes in 3 months, most of which was done by a community of more than 100 citizen developers.鈥�

鈥淭hat鈥檚 great, but let鈥檚 talk about benefits. We count more than 900 workdays saved, and more than 400 development days saved in just a year鈥檚 time. We鈥檝e seen a 35% gain in developer efficiency and 20% faster execution of our jobs. And we鈥檝e saved more than 13,000 trees. All in one year,鈥� concluded Nanavati.

The story of Mahindra & Mahindra shows the power of a workforce that has been empowered to make real change to their IT systems and the tangible results that can be realised. And with the ability to link low-code, no-code development with pro-code development via and , as well as increasing amounts of natural language interaction through , it is easier than ever to modernise processes fast.

C is for Clean Core

At SAP, we know better than most that enterprise systems can be complex. That鈥檚 why a 鈥� a cloud compliant, modern, flexible ERP that can be updated and scaled simply 鈥� is at the centre of our strategy.

And it鈥檚 a concept that鈥檚 also at the heart of the future strategic direction for all of our customers.

Takuya Sakai, CIO of , embodies that more than most. His company has used 51风流ERP globally for more than 20 years, over which time the system became more and more complex.

鈥淭hat complexity incurred significant maintenance costs, prevented the company from quickly introducing new innovation, and ultimately hindered its growth,鈥� said Sakai-san. 鈥淚t was very critical to reduce the complexity.鈥�

Using 51风流Business Technology Platform (BTP), Hitachi HiTech was able to easily upgrade 51风流S/4HANA systems in the public and private cloud 鈥� at the same time reducing the number of add-ons and customisations in the software down from 9,000 to just 800.

鈥淯sing 51风流BTP we can build smart, global digital processes without touching the 51风流S/4HANA core. 51风流BTP is a very, very important tool to accelerate our business processes,鈥� concluded Sakai-san.

What鈥檚 next: AI for business, not AI for AI鈥檚 sake

听It鈥檚 easy to get carried away by hype and excitement, especially around innovation like generative AI.

But what I saw at 51风流TechEd was even more exciting 鈥� new innovations, here today, that are already making a tangible difference to real business problems.

The key is in the context 鈥� using your AI to connect data, not just collect it. By generating reliable, responsible insights that understand the context of the business processes that surround them, Business AI will help boost productivity, efficiency, and real outcomes.

Read more about the new announcements at .

The post What You Might Have Missed at 51风流TechEd 2023: Remember Your ABCs appeared first on 51风流Africa News Center.

51风流SE unveiled a comprehensive suite of generative AI capabilities and innovations, intending to empower developers of varying skill levels to elevate their businesses in the age of AI during the 2023 51风流TechEd event.

Today鈥檚 dynamic technology and business landscape means every developer needs to be an AI developer,鈥� said Juergen Mueller, Chief Technology Officer and member of the Executive Board of 51风流SE. 鈥淭he innovations we鈥檙e launching at 51风流TechEd, from AI-infused pro-code tools to a one-stop shop to create generative AI extensions and applications on 51风流Business Technology Platform, supporting the developers at the heart of the AI revolution and providing them with resources they need to transform the way businesses run.鈥�

51风流has introduced 51风流Build Code solutions, designed to enhance collaboration between developers and business experts. These AI-powered tools streamline productivity, focusing on Java and JavaScript development, and leverage SAP鈥檚 generative AI co-pilot, Joule, to embed code generation features for data models, application logic, and test scripts.

In the realm of AI, quality data is paramount. 51风流HANA Cloud enhances its data offerings by adding new vector database features to its multimodel offerings at no extra cost. These vector data stores effectively manage unstructured data, such as text, images, or audio, providing long-term memory and improved context for AI models. These enhancements allow users to quickly locate and retrieve similar objects, facilitating tasks like searching for suppliers based on language within contracts. The vector database features foster better interaction between large language models and a company鈥檚 critical data, enhancing data insights within a secure, private framework.

To further empower developers, 51风流introduces the AI Foundation on 51风流BTP, a comprehensive platform for creating AI- and generative AI-powered extensions and applications on 51风流BTP. This platform includes everything developers need, from ready-to-use AI services and access to large language models to vector database capabilities and AI runtime and lifecycle management.

To meet the growing demand for skilled developers amid rapid tech innovation, 51风流is enhancing learning with role-based certification and free resources for ABAP Cloud developers, promoting agility and cloud compatibility.

51风流joined Stanford HAI, fostering collaboration between 51风流experts and Stanford academics in the field of Human-Centered AI. This collaboration focuses on the intersection of generative AI and business, furthering advancements in this field.

The post 51风流TechEd 2023: Comprehensive Generative AI Tools for Developers appeared first on 51风流Africa News Center.

BANGALORE, India 鈥� Nov. 2, 2023 鈥�At the 51风流TechEd event in 2023, (NYSE: SAP)听announced a comprehensive series of generative AI capabilities and advancements aimed at听empowering developers of all skill levels to supercharge their businesses in the age of AI.

鈥淭oday鈥檚 dynamic technology and business landscape means every developer needs to be an AI developer,鈥� said Juergen Mueller, Chief Technology Officer and member of the Executive Board of 51风流SE. 鈥淭he innovations we鈥檙e launching at 51风流TechEd, from AI-infused pro-code tools to a one-stop shop to create generative AI extensions and applications on 51风流Business Technology Platform, supporting the developers at the heart of the AI revolution and providing them with resources they need to transform the way businesses run.鈥�

As organisations aim to derive business value from generative AI, effective collaboration between听professional and citizen developers is essential. 51风流is launching 51风流Build Code solutions, which streamline cooperation with business experts who use the low-code 51风流Build solutions launched at SAP听TechEd in 2022. Uniquely built for 51风流applications and the 51风流ecosystem, 51风流Build Code solutions听offer AI-powered productivity tools for developers and are optimised for Java and JavaScript听development. 51风流Build Code also draws on the power of SAP鈥檚 new generative AI co-pilot Joule 鈥� the听co-pilot that truly understands business 鈥� to further boost productivity, embedding code generation听capabilities for data model, application logic and test script creation.

Good data is the foundation of good AI, and 51风流HANA Cloud continues to pioneer innovation in the data space by adding new vector database features to its multimodel offerings at no additional cost. Vector听data stores manage unstructured data 鈥� such as text, images or audio 鈥� to provide long-term memory and better context to AI models. This makes it easy to find and retrieve similar objects quickly. For example, users can search for suppliers based on the language in their contracts to examine payment history and trace individual orders. These powerful new vector database features enhance interactions between large language models and an organisation鈥檚 mission-critical data. The innovation helps put 51风流developers at the forefront of delivering radically new levels of data insight within a secure, private framework that uses industry-specific customer data to reduce hallucinations.

AI Foundation on 51风流BTP, a new one-stop shop for developers to create AI- and generative AI-powered extensions and applications on 51风流BTP, will further help increase developers鈥� impact and efficiency. AI foundation includes everything developers need to start creating business-ready AI tools on 51风流BTP 鈥� from ready-to-use AI services and access to the top large language models to vector database capabilities and AI runtime and lifecycle management.

The rapid pace of technological innovation has driven up global demand for skilled developers 鈥� and 51风流is increasing its learning opportunities in tandem. As part of a commitment to upskill two million professionals by 2025 and complement free AI learning content already available, 51风流today launched and free learning resources for back-end developers using the ABAP Cloud development model. The two new learning resources covering ABAP development tools on 51风流BTP and 51风流S/4HANA are available on the . They are designed for agile and cloud-compliant business transformation, providing developers with skills to build cloud-ready extensions that are aligned with SAP鈥檚 clean core strategy.

51风流has joined the Stanford HAI (Institute for Human-Centered AI) . Researchers and engineers at 51风流will work with the Stanford academic community, including research faculty and students, on the intersection of generative AI and business.

For details on all the announcements made at 51风流TechEd in 2023, please visit our news guide .

Visit the 51风流News Center. Follow 51风流at .

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