The comments were made by Sunil Geness, director of global government affairs and CSR at 51����Africa, and Sergio Maccotta, senior VP and GM for 51����Middle East and Africa – South.

Geness and Maccotta said businesses that can sense change, make decisions and act with minimal human intervention are reshaping how companies operate and compete. According to SAP, autonomous operations – where nearly half of all business processes run independently and most operational work is��automated��or AI-augmented – are being deployed across finance, supply chain and human resources in industries including energy, retail and manufacturing.

“This is made possible through AI embedded within enterprise resource planning processes, from finance and procurement to supply chain and HR systems, that understand context and act autonomously,” said Maccotta. “Self-optimising systems that learn, improve and adapt in real-time are matched to clean-core ERP architecture to give organisations simplified, cloud-based systems that drive profitability, reduce risk and enhance decision-making.”

51����cited data from����indicating that the global autonomous enterprise market is projected to grow from about $49 billion in 2024 to more than $118 billion by 2030, with adoption accelerating across Europe, the Middle East and Africa.

The company said while few surveys use “autonomous enterprise” as a formal category, data on AI, ERP and AI agents reflects technologies underpinning autonomous models.

Recent data for the Middle East and Africa region indicates a market size set to grow at a compound annual growth rate of 8.7%, reaching $10.2 billion by 2032.

“AI is enhancing efficiency and fostering innovation across industries, from automating routine tasks to enabling complex data analysis and providing predictive insights, while also improving decision-making and optimising business operations,” Geness said.

51����added that some analysts estimate AI could contribute $1.5 trillion to Africa’s economy if the continent captures 10% of the global AI market by 2030.

Data sovereignty

51����executives said Africa’s digital transformation continues, with data sovereignty emerging as a key factor.

“For multinational organisations and technology companies, success depends on the ability to localise without losing global efficiency, to build trust while maintaining innovation, and to invest strategically in infrastructure and partnerships that align with both regulatory demands and customer expectations,” Maccotta added.

The company said Africa’s data centre market is projected to exceed $9 billion by 2029, although it remains a small share of the global total.

Executives said autonomy does not eliminate human roles but changes them, shifting employees from managing repetitive processes to supervising systems and making strategic decisions.

Maccotta advises business leaders seeking to build autonomous enterprises to start by modernising the core and fixing the data foundation for AI-driven innovation.

“Remember that technology is only part of the story, and that the strategy, people and partners that businesses choose are as important to building a truly connected autonomous enterprise. Focus then on automating processes that protect revenue, improve cashflow or unlock capacity first, and take care to prepare people by prioritising reskilling and upskilling.

“Finally, collaborate with technology partners that act more as advisors than vendors, and can guide the process of redesigning core business processes for the AI era. True transformation happens when businesses combine intelligent systems with visionary leadership, skilled people and trusted partnerships.”

This article first appeared in .

The post Autonomous Enterprise to Define Competitive Edge in 2026 appeared first on 51����Africa News Center.

Many companies sit with years of technical debt, complex hybrid environments, disconnected��systems��and inconsistent metadata that make it difficult to build a reliable view of the��business. Businesses still grapple with ageing applications that cannot integrate with cloud platforms, while siloed departmental��systems��prevent teams from accessing the full picture needed for AI-driven decision-making.

The result is predictable: stalled AI��projects, unreliable outputs, and limited return on investment.

The need for a unified data foundation

The typical South African enterprise runs a mix of cloud��services, on-premises applications and bespoke��systems��that were built years ago to solve specific operational needs. While these��systems��may still work, they often lack the interoperability required to support modern AI initiatives. Data is stored in inconsistent formats, lack proper metadata, and often depend on manual extraction processes that strip away the��business��logic that AI models need to understand the context of the data and what it really represents.

This fragmentation affects everything from��financial��reporting to customer experience. Without a single, trusted view of data, predictive models become unreliable, automated processes fail, and teams lose confidence in machine-generated insights. For AI to scale, data must be complete, consistent, governed and accessible across the organisation.

An IDC report commissioned by Seagate previously found that��up to 68% of available enterprise data goes unused.

Modern data platforms address this by connecting all enterprise��systems, preserving��business��context, enabling real-time data access and allowing organisations to integrate with other providers. The outcome is a unified data fabric that supports analytics, applications and AI at scale.

Preparing��business��data for AI

Building��an AI-ready data foundation doesn’t happen by accident. It requires a deliberate, structured approach, following these five steps:

1 Assess the current data landscape

The first step is understanding what exists today. This means cataloguing data sources, identifying owners, documenting quality issues, and assessing integration gaps. It also involves mapping AI use cases to data requirements so that data preparation can be prioritised and aligned to real��business��needs.

For South African organisations with complex legacy environments, this assessment is essential to uncover hidden dependencies and address high-risk limitations early in the process.

2 Establish clear data governance and quality standards

Reliable data requires strong governance. Organisations should define roles, responsibilities and policies governing data access,��security, metadata and quality. This includes setting measurable standards for completeness, accuracy and consistency, supported by automated profiling tools. Metadata management is particularly critical: without clear definitions and lineage, teams cannot trust or effectively use the data.

Governance should also reflect South��Africa’s regulatory��environment, including POPIA requirements around privacy and��security.

3 Integrate and unify disconnected data sources

The next step is breaking down silos. Modern integration tools such as those built into SAP��Business��Data Cloud allow organisations to connect 51����and non-SAP��systems, unify data across cloud and on-premises environments, and maintain the��business��meaning of data as it moves.

This unified layer eliminates duplication, reduces manual extraction processes, and ensures teams work from a consistent, shared version of the truth. Real-time integration capabilities are especially important for AI models that need up-to-date information to make accurate predictions.

4 Clean, enrich and transform data

Raw data is rarely ready for AI. It must be cleaned, enriched and transformed, including correcting errors, removing duplicates, filling missing values and standardising formats. Organisations should also create new features that allow AI models to identify patterns more effectively and incorporate additional context from internal or external sources.

South African businesses with extensive unstructured data, such as PDF reports, invoices or call centre notes, should prioritise converting this content into structured formats for easy ingestion into AI models.

5 Validate, monitor and maintain data��pipelines

Even the cleanest dataset will deteriorate if not continuously monitored. Organisations should validate data before it feeds AI models, track data quality in real time, and monitor for drift or anomalies that can degrade model performance.

Automated governance tools help maintain data integrity, while clear documentation ensures teams understand how data is sourced, processed and used. Regular monitoring is essential in environments where��systems, processes and regulations frequently change.

Getting the data foundation right is a technical requirement and a strategic imperative. The organisations that prioritise data quality, integration and governance today will be the ones that scale AI confidently tomorrow, reducing risk, improving performance and unlocking new opportunities for��innovation��in an increasingly competitive market.

The post Practical Steps to Building a Data Foundation for Business AI appeared first on 51����Africa News Center.

The era of digitisation is giving way to something more profound: the Autonomous Enterprise��–��a business that can sense change, make decisions and act with minimal human intervention, all while empowering people to pursue revenue-driving strategic activities.

Autonomous operations are already being deployed across finance, supply chain, human resources, an in Industries like Energy, Retail and Manufacturing. In 2026, they will separate the most resilient and profitable businesses from the rest.

An Autonomous Enterprise goes beyond automating individual tasks by integrating autonomous ERP, business AI and clean data into the core of business operations. More than 50% of business processes run independently, and up to 80% of operational work is automated or AI-augmented.

This is made possible through AI embedded within enterprise resource planning processes, from finance and procurement, to supply chain and HR systems, that understand context and act autonomously. Self-optimising systems that learn, improve and adapt in real time, are matched to clean-core ERP architecture to give organisations simplified, cloud-based systems that drive profitability, reduce risk and enhance decision-making.

Crucially, autonomy does not remove humans: it redefines and empower their work. Employees move from managing repetitive processes to supervising intelligent systems, making strategic decisions and creating new value throughout the business.

2026 ‘a tipping point’

The year ahead will be critical for organisations across Europe, the Middle East and Africa. In Europe, business leaders face an ageing workforce, complex supply chains, regulatory pressure, and the push for sustainability and data sovereignty. Middle Eastern nations are already deploying national AI strategies and sovereign cloud infrastructure as part of a rapid diversification from the energy sector. And despite inflation and debt pressures, a world’s fastest-growing digital economy and most youthful workforce are emerging in Africa.

While the challenges in each region are unique, at their core every organisation is seeking the same capabilities: faster decision-making, greater profitability, improved resilience, and sustainability at scale.

Businesses that fail to build these capabilities, and instead rely on manual processes, disconnected systems and spreadsheets, face growing risks: slower reaction time, shrinking margins, and higher operational costs.

This is why the business opportunity for Autonomous Enterprises is significant. The global Autonomous Enterprise market is expected to grow from��, and adoption is accelerating across EMEA.

��Global partner for business transformation

While I can see the scale of the challenge businesses face to transform into autonomous enterprises, I am equally excited at bringing SAP’s strengths in this arena to bear. Through our flagship – now more accessible than ever thanks to the RISE with 51����initiative – we equip businesses with modern, clean core ERP systems that are upgrade-safe and AI ready.

, SAP’s generative AI copilot now supports 11 languages and features more than 400 embedded AI use cases across 26 industries, while the enables extensibility, data orchestration and clean core innovation for the world’s most critical industries.

My advice, to leaders seeking throughout the region to build Autonomous Enterprises, is to start modernising the core and fix the data foundation for AI-driven innovation. Remember that technology is only part of the story, and that the strategy, people and partners that businesses choose are as important to building a truly connected Autonomous Enterprise.

Focus then on automating processes that protect revenue, improve cashflow or unlock capacity first, and take care to prepare people by prioritising reskilling and upskilling. Finally, collaborate with technology partners that act more as advisors than vendors, and who can guide the process of redesigning core business processes for the AI era. True transformation happens when businesses combine intelligent systems with visionary leadership, skilled people and trusted partnerships.

In 2026, the most successful companies will go beyond digital transformation to achieve faster decision-making, greater operational certainty, and the ability to unlock new forms of growth and innovation.

This article first appeared in .

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“Uncertainty is not going away,” says , BTP product management at SAP. “You need to think about how you can transform your business for the years to come.”

At the same time, artificial intelligence (AI) is revolutionising decision-making, redefining efficiency, and helping make it easier to run the business, he adds.

“The pace of change is accelerating, and businesses are asking how they can stay ahead of the change; how they can build business that don’t just keep up with change, but thrive on it.

“The ability to adapt, to innovate, to seize opportunities is no longer an advantage, but a necessity,” Winkler says.

He believes that, to be resilient and navigate uncertainty, companies need to embrace entrepreneurial skills.

“We believe that in this time of change and technology disruption, entrepreneurial skills are more relevant than ever in small or corporate organisations.

“The first key skill is courage,” Winkler says. “This is about being adaptable, having no fear, and moving forward in a focused and lean way.”

The second is resourcefulness. “Ensure you have the right resources in place, to accomplish a lot with few resources, and to execute on anything.”

The third key skill needed in this fast-changing world is self-discipline. “Be self-driven,” Winkler says. “Think about transformation from a technology point of view, but prioritise what is important for the business.”

At the same time, organisations need to be very clear about the way they want to go forward, Winkler adds. “Clarity is needed now more than ever – not as a choice, but a necessity. Be clear about your transformation and about what you want to achieve.”

Winkler explains that is the foundation on which the company has built its technology and transformation ecosystem.

As the foundation that underpins Business Suite, Business Data Cloud, and Business AI, BTP allows organisations to integrate and extend business applications faster; create business-relevant apps; and innovate and accelerate with AI.

Winkler points out that it is a unified platform available as public cloud or multi-cloud that harmonises 51����and non-51����applications, empowering customers and partners to innovate.

BTP is powered by more than 90 applications and services.

There are currently 33��000 customers on 51����BTP, including 66% of the largest companies in the market.

New on 51����BTP is better integration between 51����Build and 51����S/4 HANA. The company has also introduced additional AI features with Joule for Developers.

In addition, 51����is continuously adding BTP to new data centres and regions. It has already built out to seven new regions this year, with more on the cards.

There is more functionality for users and more AI available for 51����S/4 HANA Cloud.

More features are available in 51����Business Data Cloud (BDC), and SAP’s Integration Suite makes it easier for customers to bring their ecosystem together.

The new releases are especially relevant for developers.

51����Build now offers the ability to create Joule Skills and AI Agents – Joule Skills where the process path is known, and AI Agents where it isn’t.

“Now, developers are able to enhance Joule’s out-of-the-box capabilities to support organisation-specific workflows,” Winkler says. “They can deploy, monitor and manage their own Joule Skills in 51����Build. “And, with the agent builder in Joule Studio they can build their own customised AI Agents.”

There are also new features to help ABAP developers ��improve their efficiency. “In the ABAP cloud environment, we have released intelligent features that help developerss with testing, and Joule will even offer recommendation to improve code.”

Further enhancements improve developer efficiency in ��51����HANA Cloud, helping them to make smart decisions while handling large amounts of interconnected data to achieve meaningful outcome.

“BTP addresses the challenges of digital transformation and helps to accelerate customers’ move to the cloud,” Winkler says. “It helps customers to optimise and integrate processes so they can innovate while keeping the core clean.

“This empowers them to unlock the power of business data and AI.”

This article first appeared on .

The post A Solid Platform Enables Innovation appeared first on 51����Africa News Center.

This is because, today, technology is transforming transformation, says , vice-president and global innovation analyst at SAP.

And today, transformative technology is all about artificial intelligence (AI).

“Experts agree that AI is the third great wave of technology after the personal computer (PC) in the 1980s and the Internet in the 1990s,” Elliott says.

“But if you are not careful, waves can come crashing down on top of you. AI is very powerful, and can have unintended consequences.”

Although it is most obvious in the visual context, AI is progressing in all directions, Elloitt points out. “The process of rapid technological change and disruption is coming to your industry and your line of business.”

Today, what’s holding up AI disruption is the fact that the rest of the ecosystem isn’t able to change as quickly.

“It’s a bit like parachuting a Formula 1 car into a medieval village. You can’t use the technology because the rest of the ecosystem isn’t there.

“In fact, if AI stopped progressing right now, we couldn’t use it to its full potential for 10 years.”

For this reason, Elliott says AI could be taken to stand for accelerate innovation. “We should use AI to adopt AI.”

Today, a lot of AI and innovation in general is handmade, with developers all starting from scratch and working on one thing.

“To accelerate the adoption, we need to move to modern assembly lines, so we can use the AI faster,” Elliott says.

He adds that 51����provides the machines to build the technology.

“We offer things like the S, where customers create data that is harmonised in the Business Data Cloud, used to ground AI, which then goes to making a better application. And, as you create applications, you can add customisation.”

51����embeds AI in all its applications, and these are available to customers right now, Elliott adds.

“But innovation is not actually about technology,” he explains. “What is holding us back is the time, skills, and resources needed to exploit the technology.”

Again, the 51����Business Technology Platform can help, with 51����Build offering aided innovation – another possible use for AI – for agile application development and customisation.

“We have the resources that can multiply efforts, let developers do more, faster, with customisations and extensions in the cloud.

“And now you can do it in natural language, because it is designed for professional developers and also business users.”

AI could also stand for automated identity, Elliott says.

And it could represent automatic integration as well. “51����Integration Suite is about AI-powered connections. It will do most of the heavy lifting in connecting system to one another.”

Meanwhile, the 51����BTP AI Foundation is a generative AI (GenAI) hub that gives customers everything they need to orchestrate customised AI, with a wide choice of models, grounding, data masking, filtering, prompt management, and lifecycle management.

At the core of any transformation is data, which is everyone recognises is important. “In fact, it is really important,” Elliott says. “It is the essential input for AI in particular.

“So AI has to stand for accurate information. AI is useless without accurate information in realtime.”

But there isn’t a company on the planet that doesn’t have a data quality problem, he adds.

“It is not a new problem, we know it’s hard to get budget to fix data. But this is an opportunity to ask for money to do just that. Now is a great time to establish governance, data ownership, and all the things you have wanted to do for years.”

The second big problem is integrating data – which is also not a new problem.

“This is where comes in,” Elliott says. “And we offer it as a service, so we can do more of it for you – integrate data from 51����applications and also external data.”

The helps with relationship extraction. “You already have this information, now we are gathering it and exposing it, and putting it in a format that you can use for your AI,” Elliott explains.

AI could also represent analytics improved, which is why 51����Analytics Cloud has the GenAI-powered Just Ask feature.

“In analytics, there is a dream of total situational awareness. Of bringing in data from all sources, but having overall vision. AI can be used to connect data and deal with fuzziness.”

AI could also stand for agents incoming. “This is the next generation of AI, moving along from the current efficient processes with pre-defined steps. But these processes can’t deal with ambiguity. Agents, on the other hand, can reason through what it needs to do next. So the processes and data can be a lot more unstructured than before.”

Another interpretation of AI could be agents for business, Elliott adds. “This is the next evolutionary step – in fact, some companies are already doing it – using AI to get rid of a lot of manual work.”

AI could be used for automatic innovation. “We have incredible amounts of information and amazing intelligence,” says Elliott. “So why not let the systems tell us what we should do next?

“We are starting to get there, and you can already get great automated system insights. And 51����also has best practices, so we can provide customers with that out of the box.”

Once that is in place, and customers need to implement their systems, automated implementation could be the final meaning for AI.

“Of course, technology is not everything,” Elliott points out. “You need to get people to adopt new ways of working – and AI is good for adoption optimisation and change management.”

In conclusion, Elliott believes that AI today is like a staircase. “You have to take one step after the other. But in the future it will be more like an escalator.”

The key to successful AI adoption lies not in the technology he adds, but in the people, culture, and organisation.

“No matter how much you have invested in adoption, culture, and change management – invest more.”

This article first appeared on .

The post How AI is Transforming Digital Transformation appeared first on 51����Africa News Center.

51����SE��(NYSE: SAP) announced that VFS Global, the world-leading provider of visa, consular and technology services to governments and diplomatic missions, will leverage 51����software to help it develop leading-edge AI-powered digital solutions for cross-border mobility and citizen services.

Cross-border mobility and citizen services are becoming increasingly digital, and governments are looking into the use of innovative technologies such as artificial intelligence to drive efficiency and sovereign security. To accelerate its innovation road map and help governments meet the increasingly complex needs of travelers and citizens, VFS Global is adopting 51����S/4HANA Cloud Public Edition and other 51����solutions.

“We take great pride in partnering with 51����as a leading and trusted technology and AI company,” said Zubin Karkaria, founder and CEO of VFS Global. “By combining our deep expertise in visa, consular and citizen services with SAP’s world-class solutions, we empower governments to enhance efficiency, strengthen security and enable seamless mobility for millions of travelers around the world.”

“With 51����solutions at its core, VFS will be able to leverage the latest innovations to become an even stronger partner for governments, travelers and citizens worldwide,” said Christian Klein, CEO of 51����SE.

In line with its vision to embrace technological innovation to support governments and diplomatic missions worldwide, VFS Global has also chosen 51����Business Technology Platform and the 51����Business Data Cloud solution to deliver leading-edge and AI-powered solutions to its customers and to drive operational excellence across its global operations.

“By combining the strengths of VFS Global and SAP, we are elevating cross-border mobility and citizen��services to the next level”, said Michael Nilles, member of the VFS executive board and chief digital and technology officer. “Strategically, this positions us as a leading force in shaping the future of GovTech and TravelTech, powered by technology and AI innovations that benefit governments, travelers and citizens worldwide,” he added.

The post VFS Global Leverages 51����Software to Power Digital Cross-border Mobility appeared first on 51����Africa News Center.

Gaming is something that keeps inspiring me. I’m amazed by the speed, accuracy, and level of concentration of professional players. It’s impressive how this industry has evolved and grown over just a couple of decades.��

commands an imposing presence in the esports world, boasting over 160 professional players across more than 15 different games and a staggering fan base of over 10 million followers on various social media platforms. With more than 75 premier events won, Team Liquid is one of the most successful organizations in competitive gaming.��

The game with the highest viewership and extensive fandom is League of Legends. Team Liquid successfully competes with their League of Legends team, which recently won the League of Legends Championship Series (LCS) 2024 Spring tournament.��

In League of Legends, the goal is to create a strong and balanced team consisting of five characters, called “champions,” in order to outplay and outsmart the opponents during the game by being one step ahead of competition.��

Teams participate in a pre-game draft process to select champions before a match. This involves banning and picking champions from a pool of 166 choices to create a strong team.��

Champions are the in-game figures controlled by each player. Each champion has particular skills and areas in which they excel. Putting the champions together allows the team to play in various strategic directions to win the match.��

After choosing five champions (“pick”), each team is also allowed to remove five champions from the pool (“ban”). Those players cannot be picked by either side. This can be utilized to remove specific parts that would otherwise counter a strategy or hinder the other team from playing their favorite style and/or composition.��

Esports teams and their analysts need to prepare for the draft process, as it requires knowledge of the opponent’s favorite picks and strategies. Imagine a five-a-side dodgeball match, but before the match begins, the five players from each team draw their champions from a pool of 166 individual champions.��

With bi-weekly updates to the game (“patches”), especially affecting the champions as well as indirectly teams practicing and developing new strategies, competitive League of Legends is an ever-changing game. It creates the need to constantly adapt your draft to a new environment, to analyze both your own and the opposing team’s behavior.��

Furthermore, the nature of the draft process and the varying strategies of opponents make accurate predictions difficult. Esports teams have only a week to prepare for the game and gather knowledge about the other team’s favorite champion picks, strengths, and weaknesses.��

Previously, Team Liquid coaches prepared draft scenarios based on manual analysis of the opponent team’s draft behaviors and champion preferences. However, the challenge was that manual analysis is done before the draft, with the best potential pick or ban changes based on the decisions of the other team. Additionally, the sheer number of potential matches to choose from and the different strategies employed by opponent teams make manual draft prediction very difficult.��

51����Helps Change the Game��

What if Team Liquid could analyze in seconds the best choice for upcoming drafts, including picks and bans, while considering more than 6,000 professional esports matches from the past year? What if the analysis would also consider the impact of game patches from the publishers by taking an additional 1.6 million amateur matches into account to assess changes in the power attributes and strengths of the champions? With SAP, this is now a reality.��

By using 51����AI Core to train a generative AI model that takes data from past matches and puts them into context of the upcoming game, Team Liquid gets suggestions of the best draft picks and bans to maximize the chances to win.��

The solution is built on 51����Business Technology Platform (51����BTP), and the data is stored in 51����HANA Cloud to cope with the 1.6 terabyte game data from past games. The result is an intelligent draft bot training, an application that runs on 51����BTP, visualizes the predictions, and provides Team Liquid with the current winning probability after each pick and ban.��

Manual Analysis Is a Thing of the Past��

With the AI draft bot, Team Liquid can train for draft situations against any professional team they face in a matter of seconds. This is achieved by incorporating multiple influencing factors based on an unprecedented number of matches. The coaches and players benefit from the opportunity to conduct what-if analyses and derive valuable knowledge from the data to simulate new strategies. This is also reflected in the time saved compared to the previous manual analysis: Team Liquid saves approximately 10,000 hours per year per year with the solutions from SAP.��

Relying on 51����BTP and 51����HANA Cloud, 51����Business AI provides Team Liquid with the opportunity to further improve their game by leveraging data to make more informed decisions. Here is where fun and business meet.��

This is how the power of business AI is made tangible in a perfect way — not just for gamers.

This article first appeared on the 51����News Center.��

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By examining innovative solutions, such as and the concept of a data fabric, we uncover how organisations can transcend traditional barriers, harness the full potential of their data assets, and pave the way for enhanced efficiency and competitiveness.

has seamlessly implemented Datasphere at clients and a highly-effective data-driven strategy, which has already demonstrated its immense impact and power.

As businesses aim to implement data-driven strategies, it is crucial to break down the silos that exist between different data sources. Doing so will unlock the full potential of their data assets and give them a competitive advantage in today’s digital world. With the plethora of tools available today, it is easier than ever to extract valuable insights from your own data.

For clients with multiple data hubs on heterogeneous cloud environments, including investments, the business data fabric can now help eliminate silos and lead to more significant efficiency gains.

The business data fabric provides great value to customers by simplifying the delivery of accurate data in business terms, even when dealing with highly-distributed data landscapes. This means that business innovation is no longer limited by the location of data, slowed down by the creation of new data staging plans, or hindered by incomplete business context.

A data fabric is an advanced data management architecture that allows organisations to integrate large volumes of data from various sources. It provides a consistent and reliable way to access, analyse and share data across the organisation.

With a data fabric, users of all skill levels can easily access and make sense of complex data sets, enabling them to make informed decisions based on accurate and relevant information. This can lead to improved business outcomes, increased productivity and gain a competitive advantage in the market.

Integrating AI in business operations will undoubtedly prove to be a game-changer. By offering rapid insights and enabling prompt decision-making, AI has the potential to revolutionise the way businesses operate.

The power of AI in the world of data warehousing is truly awe-inspiring, as it offers unparalleled insights on the fly. Think of it as a copilot that can assist you in determining, guiding and achieving your goals.

The new AI copilot, , in and , as well as the , enables users to find hidden insights and patterns in complex data.

It is a platform designed to be open and flexible, allowing for seamless integration with a diverse range of sources and technologies. 51����has announced partnerships with , , , and to simplify customers’ data landscapes.

By integrating their data and AI platforms with 51����Datasphere, organisations can now access their mission-critical business data across any cloud infrastructure in an open data ecosystem.

51����Datasphere is a comprehensive data management platform that provides a centralised solution for all your data-related needs. With 51����Datasphere, you can easily access, integrate and analyse your data in a single location, without the need for managing multiple silos. This means that you no longer need to spend countless hours tracking down information from disparate sources, but instead can focus on deriving insights and making data-driven decisions.

The ability to access data in real-time, integrated across various business functions, has been a crucial development in advancing global business innovation. Our clients can now work seamlessly with 51����Datasphere and make the most of our existing portfolio of data platforms, business intelligence, and planning analysis solutions. This enables them to move beyond manual and siloed analysis processes and optimise their target revenue and GP, sales goals, and operational capacity requirements. With this approach, they can effectively harness their data to achieve their business objectives.

Contact Decision Inc. today to explore how the 51����Datasphere Platform can empower your organisation’s growth journey.

The post Paving the Way for Data Management Through 51����Datasphere appeared first on 51����Africa News Center.

“Capturing data to make better decisions is an enterprise technology imperative that’s become increasingly critical as AI – which relies on quality data – revolutionizes every aspect of business,” said Juergen Mueller, 51����Chief Technology Officer and member of the Executive Board. “Our newest 51����Datasphere innovations, as well as an expanded partnership with Collibra, represents a quantum leap in our ability to help customers drive intelligent business transformations through data.”

At the heart of these announcements is the business data fabric, an architecture that helps ensure data is not just an asset but also the core underpinning of strategic initiatives. The innovations and partnership announced today equip organizations to deliver meaningful data to data consumers – with business context and logic intact.

“We have decided to leverage 51����Datasphere for a modern business data fabric architecture in conjunction with our 51����S/4HANA landscape. It allows us to effectively establish a modern data analytics platform that enables a business self service capability on the basis of trusted data and data models,” said Achim Welter, Senior Director ERP, Digital & IT Strategy, Hershey’s.

Today’s 51����Datasphere innovations help customers achieve a unified data view that simplifies their data landscapes while retaining context and logic – enabling them to adapt faster to market changes and make more-efficient decisions. From new copilot and vector database capabilities that help ensure business context remains constant in generative AI outputs to a new knowledge graph that helps uncover insights and patterns in complex data, SAP’s data innovations help ensure customers have the full power of their data at their fingertips.

Today’s key innovations include:

Generative-AI Copilot and AI Governance

SAP’s generative-AI assistant, the copilot, is now coming to the 51����Analytics Cloud solution to automate the creation and development of reports, dashboards, plans and more. This automation is enabled by the 51����HANA Cloud vector engine capabilities, which combine the power of large language models with the relevant data of your organization – helping ensure business context is a constant for generative-AI outputs.

Incorporating generative AI across the business isn’t possible without trusted and governed data. To provide organizations with a solution to govern the policies, processes and practices of AI, 51����is announcing an expansion of our partnership with Collibra to integrate Collibra’s AI Governance with 51����data assets. This can help provide transparency and accountability for organizations and help ensure regulatory, compliance and privacy policies are met.

Discover Hidden Insights and Patterns with Knowledge Graph

With the new 51����Datasphere knowledge graph, organizations can discover hidden insights and patterns across their applications and systems. This enables both technical and business users to deeply understand the relationships between data, metadata and business processes, as well as boost the effectiveness of machine learning and large language models.

Unified and Advanced Planning and Analytics

The new 51����Datasphere integration with 51����Analytics Cloud offers a single data management system and advanced analytics to power cross-organizational planning. Planners can leverage a single flexible model to break down silos between planning using one tool for data preparation, modeling and planning.

Additionally, business users can use the new compass capability in 51����Analytics Cloud to realize better outcomes in planning and analytics through data-driven simulation. It enables organizations to run complex simulations using a chat interface to evaluate predictive outcomes and continually adjust controllable variables to find the optimal plan.

This supports customers to transform their planning by unifying financial, operational, supply chain and workforce planning with native connection to 51����applications and third-party data.

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The post 51����Shapes the Future of Data-Driven Business Transformation with Innovations that Equip Customers to Succeed in the Era of AI appeared first on 51����Africa News Center.

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’s 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����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.

The post Why We Need to Safeguard AI’s Future with Dependable Data appeared first on 51����Africa News Center.