{"id":1915,"date":"2025-01-02T18:48:31","date_gmt":"2025-01-02T18:48:31","guid":{"rendered":"https:\/\/solutionsreview.com\/thought-leaders\/?p=1915"},"modified":"2025-01-02T18:52:45","modified_gmt":"2025-01-02T18:52:45","slug":"data-and-ai-strategy-for-2025-time-to-ditch-old-school-thinking","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/thought-leaders\/data-and-ai-strategy-for-2025-time-to-ditch-old-school-thinking\/","title":{"rendered":"Data and AI Strategy for 2025: Time to Ditch Old School Thinking"},"content":{"rendered":"

\"\"<\/p>\n

In my last podcast on The Data Strategy Show<\/a>, I spoke to Malcolm Hawker and one of the subjects that came up was \u201cmindset.\u201d<\/p>\n

In the last article of 2024, I wanted to look ahead at 2025 and reflect on the mindset that is required for the coming year and how organizations need to progress in their data and AI strategies.<\/p>\n

If we know anything about the past it\u2019s the fact that many an organisation tends to keep doing the same thing expecting a different result. That can\u2019t go on any longer as AI is no longer a concept confined to experimental projects; it\u2019s an engine for business transformation. Not that it hasn\u2019t been in the context of Machine Learning, but what I see is many companies being stuck in the past, applying outdated thinking to an emerging playing field.<\/p>\n

As we approach 2025, the companies that succeed will be the ones strong and bold enough to abandon their old-school approaches and rethink their data and AI strategies. Those that don’t will find themselves irrelevant and in the mire with an unpleasant odour as my old professor used to say when my reasoning wasn\u2019t quite up to snuff!<\/p>\n

Why the Old School Approach is Failing<\/strong><\/h4>\n

Most organizations still treat data and AI as standalone initiatives, technical projects to be executed in silos. They obsess over:<\/p>\n

    \n
  • Building a data platform before understanding the business problem.<\/li>\n
  • Chasing “AI readiness” without a clear sense of purpose.<\/li>\n
  • Measuring success in terms of activity (dashboards built, models deployed) rather than outcomes.<\/li>\n<\/ul>\n

    This mindset is why many data and AI initiatives fail to deliver value. It’s why CEOs complain about the investment committed while their teams churn out models no one uses.<\/p>\n

    What Kind of Mindset is Needed for 2025<\/strong><\/h4>\n

    To thrive in this new era of AI, businesses need a fundamental mindset shift. As I always say AI isn\u2019t magic, and it isn\u2019t a side project. It\u2019s a tool for solving real business problems, and your strategy needs to reflect that.<\/p>\n

    This new mindset, doesn\u2019t need a new sexy approach, it just needs a bit of common sense, which isn\u2019t lacking in organisations at all. I have been using frameworks and approaches in my work for over 20 years, when things don\u2019t work or they go out of date, I review them and make changes, or work with my clients to review what works, what needs to be chucked out with the bath water and what newness needs to be infused. Sometimes, it works, sometimes, it doesn\u2019t and we just need to keep iterating until we land on an approach that feels like it\u2019s the right way. So, when I think about 2025, here is an approach that has been working for a while now:<\/p>\n

      \n
    1. Business-Led, Not Tech-Led<\/strong>: Start with the value you want to create, not the technology you want to use.<\/li>\n
    2. Integrated Thinking<\/strong>: Your data and AI strategy must be inseparable from your business strategy.<\/li>\n
    3. Speed and Agility<\/strong>: Build strategies that deliver quick wins while keeping long-term objectives in focus.<\/li>\n
    4. Cultural Readiness<\/strong>: AI success isn\u2019t just technical. It requires change at every level of your organization.<\/span><\/li>\n<\/ol>\n

      The Key Challenges Ahead<\/strong><\/h4>\n

      Those 4 points aren\u2019t new at all, and that\u2019s why they work. But the mindset overhaul is all about challenging the current ways of working and just looking through a different lens. Here are the 3 typical challenges along with their solutions, which again isn\u2019t going to blow your mind, but it will set you up for success, which is what all organizations want:<\/p>\n

      Mindset Overhaul<\/strong><\/p>\n

        \n
      • Challenge<\/strong>: How do you move leadership and teams away from treating AI as a shiny new toy?<\/li>\n
      • Solution<\/strong>: Start with business problems and measurable outcomes. Make it impossible for anyone to ignore the value AI can bring.<\/li>\n<\/ul>\n

        Value Alignment<\/strong><\/p>\n

          \n
        • Challenge<\/strong>: Are your data and AI initiatives solving meaningful problems, or are they just pet projects?<\/li>\n
        • Solution<\/strong>: Align every AI initiative to your top business priorities. Stop chasing hype.<\/li>\n<\/ul>\n

          Organisational Resistance<\/strong><\/p>\n

            \n
          • Challenge<\/strong>: How do you embed AI into decision-making across the business?<\/li>\n
          • Solution<\/strong>: Invest in decision intelligence and ensure your teams trust and use the outputs to reach the outcomes and know how to implement the decisions they need to take and make.<\/li>\n<\/ul>\n

            A Proven Framework for 2025<\/strong><\/p>\n

            As AI starts to reshape the business landscape, many businesses can no longer afford vague aspirations or scattergun AI investments. Success in 2025 demands a clear, actionable strategy grounded in measurable value creation and ruthless prioritization.<\/p>\n

            But the truth is most organizations are fumbling in the dark. They chase tools, not outcomes. They confuse activity with progress, and worse, they waste resources on initiatives that fail to move the needle for their business.<\/p>\n

            If your data and AI strategy doesn\u2019t deliver tangible value fast, it\u2019s not a strategy. It\u2019s an expensive experiment. You need a structured approach that aligns your efforts with your organization\u2019s priorities, drives immediate impact, and builds a foundation for long-term transformation.<\/p>\n

            This framework isn\u2019t about vague theories or buzzwords. It\u2019s about getting practical, asking the right questions, and ensuring every data and AI initiative contributes directly to your organization\u2019s success.<\/p>\n

            Here\u2019s how to move from noise to clarity, from activity to outcomes, and from old-school thinking to a strategy built for 2025:<\/p>\n

              \n
            1. Define Value<\/strong>\u00a0What problems are you solving, and what outcomes do you expect? How will you measure success (e.g., revenue growth, cost savings, risk reduction)?<\/li>\n
            2. Build Business Use Cases<\/strong>\u00a0Prioritise high-value, achievable use cases that deliver quick wins. Test, iterate, and scale fast.<\/li>\n
            3. Align Operating Models<\/strong>\u00a0Do your data and AI operating models support agility and collaboration? Is your governance slowing you down or enabling value creation? (I don\u2019t mean data governance, I mean decision making)<\/li>\n
            4. Embed into the Business<\/strong>\u00a0How will AI and data be used daily to drive decision-making? Are your people equipped to trust and act on insights?<\/li>\n
            5. Measure and Adapt<\/strong>\u00a0Are you consistently measuring business outcomes, not activity? What lessons are you learning, and how are you adjusting?<\/li>\n<\/ol>\n

              The 5 Questions Every C-Suite Leader Must Ask<\/strong><\/h4>\n

              As a leader, the responsibility for your organization\u2019s data and AI strategy rests squarely on your shoulders. You can delegate the execution, but you cannot delegate the outcomes. And yet, many leaders fail to ask the right questions\u2014choosing instead to chase trends, rely on overworked teams, or pin hopes on vague promises of \u201cinnovation.\u201d<\/p>\n

              Here\u2019s the reality: if your data and AI strategy isn\u2019t delivering value, it\u2019s failing. And if you, as part of the C-suite, aren\u2019t actively challenging its direction, you\u2019re complicit in that failure.<\/p>\n

              2025 will be a defining year. The winners will be the companies whose leaders refuse to settle for mediocrity, who demand clarity and accountability, and who are brave enough to ask the tough, uncomfortable questions that uncover blind spots.<\/p>\n

              These five questions are not just checkboxes; they are the litmus test for whether your strategy is ready to compete\u2014or destined to crumble. Answer them honestly, and you\u2019ll know whether you\u2019re on the right path or heading for irrelevance.<\/p>\n

              Here\u2019s what every C-suite leader needs to confront head-on:<\/p>\n

                \n
              1. Where is the value?<\/strong>\u00a0If this project doesn\u2019t deliver measurable business value, why are we doing it?<\/li>\n
              2. Who is accountable?<\/strong>\u00a0Is ownership of AI initiatives clear, or are we passing the buck between IT and business units?<\/li>\n
              3. Are we moving fast enough?<\/strong>\u00a0How long does it take us to go from idea to implementation? Can we move faster without compromising quality?<\/li>\n
              4. Do we trust our data?<\/strong>\u00a0If teams don\u2019t trust the data, they won\u2019t use it. Are we investing enough in quality and governance?<\/li>\n
              5. Are we prepared for failure?<\/strong>\u00a0Not every initiative will succeed. How do we fail fast and learn without losing momentum?<\/li>\n<\/ol>\n

                Final Word<\/strong><\/h4>\n

                2025 will not wait for you. This is no incremental evolution, it\u2019s a new mindset that demands leaders redefine how they think about data, AI, and, most importantly, their role in driving transformation. The real challenge isn\u2019t technological; it\u2019s existential.<\/p>\n

                If your organisation is clinging to outdated strategies, hoping to squeeze value out of yesterday\u2019s playbook, you\u2019re not just falling behind, you\u2019re actively writing your own obsolescence. AI is not a tool to experiment with at the edges of your business; it\u2019s the engine that will define whether your business thrives or vanishes in the years to come.<\/p>\n

                The question is stark: do you have the courage to break free from the inertia of \u2018how we\u2019ve always done it\u2019? Are you ready to challenge your own assumptions, disrupt your own organisation, and commit to a strategy that puts value not activity at its core?<\/p>\n

                Because the truth is: if you don\u2019t disrupt yourself, the market will do it for you. And it won\u2019t be forgiving.<\/p>\n

                The time for hesitation is over.<\/p>\n

                The leaders who act with clarity and conviction today will shape the future.<\/p>\n

                The rest will become footnotes in history.<\/p>\n

                Which will you be?<\/p>\n","protected":false},"excerpt":{"rendered":"

                In my last podcast on The Data Strategy Show, I spoke to Malcolm Hawker and one of the subjects that came up was \u201cmindset.\u201d In the last article of 2024, I wanted to look ahead at 2025 and reflect on the mindset that is required for the coming year and how organizations need to progress […]<\/p>\n","protected":false},"author":546,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[10],"tags":[],"acf":[],"yoast_head":"\nData and AI Strategy for 2025: Time to Ditch Old School Thinking<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data and AI Strategy for 2025: Time to Ditch Old School Thinking\" \/>\n<meta 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