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The UK government has introduced an AI assurance platform, offering British businesses a centralized resource for guidance on identifying and managing potential risks associated with AI, as part of efforts to build trust in AI systems. billion in revenue, the UK government said. “The
AI agents are powered by the same AI systems as chatbots, but can take independent action, collaborate to achieve bigger objectives, and take over entire business workflows. The technology is relatively new, but all the major players are already on board. The next evolution of AI has arrived, and its agentic.
Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). In addition to using cloud for storage, many modern data architectures make use of cloud computing to analyze and manage data.
Most IT and business executives recognize the necessity of close alignment. They understand that their strategies, capabilities, resources, and management systems should be configured to support the enterprise’s overarching purpose and goals. Having a seat at the strategy table helps IT push the business forward. “It
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The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both. This means that the infrastructure needs to provide seamless data mobility and management across these systems. Imagine that you’re a data engineer.
In our fast-changing digital world, it’s essential to sync IT strategies with business objectives for lasting success. Technology has shifted from a back-office function to a core enabler of business growth, innovation, and competitive advantage.
Even in the case of moderate to low risk, technical debt impacts can change quickly as business needs evolve. Another question is: What separates out debt thats fixed opportunistically versus critical debt that could cripple the business? Using the companys data in LLMs, AI agents, or other generative AI models creates more risk.
Still, CIOs have reason to drive AI capabilities and employee adoption, as only 16% of companies are reinvention ready with fully modernized data foundations and end-to-end platform integration to support automation across most business processes, according to Accenture. These reinvention-ready organizations have 2.5
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Data silos, lack of standardization, and uncertainty over compliance with privacy regulations can limit accessibility and compromise data quality, but modern data management can overcome those challenges. Some of the key applications of modern data management are to assess quality, identify gaps, and organize data for AI model building.
AI is clearly making its way across the enterprise, with 49% of respondents expecting that the use of AI will be pervasive across all sectors and business functions. Having the right AI tools will help these employees manage the increasing volume and variety of data and find the competitive edge their organisations need.
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Once a strictly tech role managing an organizations internal needs, the CIO role has seen a massive tectonic shift. With technology rapidly shaping business outcomes, and the tech infrastructure supporting every aspect of business, CIOs much deservedly now occupy a seat at the table.
How and why is Ingram Micro becoming a platform business? But today, were working toward becoming a platform business, and recently re-entered the public eye under the NYSE: INGM ticker symbol. Many digital transformations focus on platforms to support the business, but thats different from running a platform business.
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AI is at the core of this vision, driving smart governance, efficient resource management, and enhanced quality of life for residents and visitors alike. In the UAE, 91% of consumers know GenAI and 34% use these technologies. Positioning the country at the forefront of AI development.
Decades-old apps designed to retain a limited amount of data due to storage costs at the time are also unlikely to integrate easily with AI tools, says Brian Klingbeil, chief strategy officer at managed services provider Ensono. In many cases, outdated apps are completely blocking AI adoption, Stone says. We are in mid-transition, Stone says.
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To help enterprises overcome these challenges and achieve positive business outcomes, EXL launched EXLerate.AI, its agentic AI platform. Its orchestrator goes beyond simply automating processes; it creates and manages them to ensure efficiency and compliance, from initial data processing to final decision-making.
For its Generative AI Readiness Report, IT services company Avanade surveyed over 3,000 business and IT executives in 10 countries from companies with at least $500 million in annual revenue. Here are key attributes of those who embody this new standard in order to succeed in the current multifaceted business environment.
Some did manage to scale agile and leverage frameworks to create process standards and improve IT practices. But the work to get business leaders, stakeholders, and end-users to shift to agile mindsets mostly got stuck. Product management addresses the complexities of market research and product strategy definition.
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Business leaders may be confident that their organizations data is ready for AI, but IT workers tell a much different story, with most spending hours each day massaging the data into shape. It says our job as technology leaders can help educate our audience on what is possible and what it will take to get to their goal.
With data central to every aspect of business, the chief data officer has become a highly strategic executive. Todays CDO is focused on helping the organization leverage data as a business asset to drive outcomes. Voorhees has seen great benefit from extending data literacy programs to include AI technologies.
According to a recent survey by Foundry , nearly all respondents (97%) reported that their organization is impacted by digital friction, defined as the unnecessary effort an employee must exert to use data or technology for work. Managed, on the other hand, it can boost operations, efficiency, and resiliency.
trillion annually — translating this into compelling business language for the board remains a persistent challenge. The more strategic concern isn’t just the cost— it’s that technical debt is affecting companies’ abilities to create new business, and saps the means to respond to shifting market conditions.
In today’s fast-evolving business landscape, environmental, social and governance (ESG) criteria have become fundamental to corporate responsibility and long-term success. Technologies such as artificial intelligence (AI), generative AI (genAI) and blockchain are revolutionizing operations.
Gartner’s top predictions for 2025 are as follows: Through 2026, 20% of organizations will use AI to flatten their organizational structure, eliminating more than half of current middle management positions. By 2029, 10% of global boards will use AI guidance to challenge executive decisions that are material to their business.
Agentic AI, the more focused alternative to general-purpose generative AI, is gaining momentum in the enterprise, with Forrester having named it a top emerging technology for 2025 in June. The technology is in its early days, and several questions remain open chief among them, how AI agents will be priced.
The past year was another one of rapid change, as economic cycles, business trends, and technology itself evolved at a breakneck pace. Smith says he has seen that transition over the past 12 months or so, saying the technology has matured to the point where it is winning over skeptics. Heres what they say.
Technology continues to advance at a furious pace. That’s great, because a strong IT environment is necessary to take advantage of the latest innovations and business opportunities. Rasmussen says the modernization process should begin by forming a strategy team and directing it to build the business case for why change is needed. “As
These services are delivered primarily by small independent businesses that have a relationship with the local community, but we implemented a common platform used across markets to foster greater visibility and effectiveness. In my next CIO role, I inherited an enablement team, which really was product management as we know it now.
Migration to the cloud, data valorization, and development of e-commerce are areas where rubber sole manufacturer Vibram has transformed its business as it opens up to new markets. Vibram certainly isn’t an isolated case of a company growing its business through tools made available by the CIO.
Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. We’re trying to get the AI to have the same knowledge as the best employee in the business,” he says.
For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes. Operational AI involves applying AI in real-world business operations, enabling end-to-end execution of AI use cases. Today, enterprises are leveraging various types of AI to achieve their goals.
Hes leveraging his vendor relationships to keep pace with emerging as well as tried-and-true technologies and practices. Deliver value from generative AI As organizations move from experimenting and testing generative AI use cases , theyre looking for gen AI to deliver real business value. But its no longer about just standing it up.
To overcome those challenges and successfully scale AI enterprise-wide, organizations must create a modern data architecture leveraging a mix of technologies, capabilities, and approaches including data lakehouses, data fabric, and data mesh. Before we go further, let’s quickly define what we mean by each of these terms.
Salima Bhimani has been encouraging the responsible and ethical use of AI for several years as Alphabet’s first chief strategist and director for inclusive and responsible technology, business, and leaders from 2017 to 2023. Are we building AI strategies that are aligned to business goals? Will it mitigate risk?
Legacy platforms meaning IT applications and platforms that businesses implemented decades ago, and which still power production workloads are what you might call the third rail of IT estates. At the same time, however, the business may have so much riding on legacy technology that it cant afford not to maintain and update it.
IT managers are often responsible for not just overseeing an organization’s IT infrastructure but its IT teams as well. To succeed, you need to understand the fundamentals of security, data storage, hardware, software, networking, and IT management frameworks — and how they all work together to deliver business value.
NTT DATAs landmark Global GenAI Report underscores how the technology is gaining momentum. Long-term game Business leaders are turning their focus from experimenting with GenAI to exploring long-term use cases that transform business performance and workplace culture for the better.
In an era where technology reshapes entire industries, I’ve had the privilege of leading Mastercard on an extraordinary journey. When I think about the technology we started working with early in my career and look at what we’ve been able to do since, it truly is amazing, a global transformation led by and driven through technology.
Celanese operates more than 50 large manufacturing plants across 27 countries, and has made several significant acquisitions in recent years, including Dupont’s $11 billion mobility and materials (M&M) business. What is the business transformation underway at Celanese? That’s not how we measure value.
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