IT is no longer just a back-office function—it’s driving innovation, creating new products, and generating revenue. AI is reshaping everything. This shift is changing IT’s role from "keeping the lights on" to becoming a core engine of business growth.
Not every organization is ready for this shift.
From Cost Center to Profit Engine
I’ve spent more than 20 years as a technology leader - practitioner, seller, advisor, researcher - and throughout that time, IT has been seen as a cost center—a necessary but expensive part of doing business. Every year, we’ve been expected to cut budgets by 10%, regardless of the value we deliver.
But AI is finally flipping that script for companies bold enough to embrace it. Goldman Sachs, for example, turned their internal risk systems into Marquee, a platform that generates revenue by serving clients externally. Similarly, Adobe has evolved from a traditional software vendor into an AI-powered creative powerhouse, reshaping its business and setting new industry standards.
These organizations didn’t just tweak their IT strategies; they completely redefined them. Instead of waiting for the market to disrupt them - they disrupted themselves. They’re proof that IT can become a core driver of business value.
That said, these examples are the exception. Most organizations are clinging to old-school models, failing to recognize that IT’s role has fundamentally changed.
The companies succeeding in this new model are doing three things:
1. Commercializing internal AI solutions.
2. Building AI-driven products and services.
3. Developing platform businesses that scale through AI.
Bottom line, IT is no longer just supporting the business—IT IS the business.
Why Old-School Companies Struggle
When I speak with executive leaders, I often come away deeply concerned—not just for their businesses, but for their own roles in the future. Many traditional organizations have significant structural issues that prevent them from adapting to the new reality of IT. Silos are deeply entrenched, with business leaders and IT teams operating in isolation, speaking different languages, and moving at completely different speeds.
Even more troubling, years of focusing on cost-cutting and maintenance have created IT leaders who are entirely defensive in their thinking. They’ve spent decades refining how to do more with less, so they lack the vision to play offense—to innovate, drive growth, and create new value. This outdated mindset is putting their businesses, and their careers, at serious risk as AI transforms the world around them.
AI demands cross-functional collaboration and hybrid roles—teams that blend business and technical expertise. Companies need people like:
• AI Product Managers who blend technical expertise with business acumen.
• Business-Technology Strategists who connect AI's capabilities with real business outcomes.
• Data Science Leaders who directly influence product strategy.
Take John Deere, for example. They don’t just treat AI as an add-on to their traditional agricultural equipment. Instead, they have embedded AI and machine learning into their core operations, from autonomous tractors to precision planting solutions. This integration allows them to provide farmers with data-driven insights that improve yields and reduce waste, fundamentally transforming their business and enabling them to stay ahead of competitors.
For companies still clinging to outdated mindsets, embedding AI across the organization will fundamentally disrupt your culture, challenging long-held ways of working and thinking.
The New Rules of Investment
Old-school companies tend to pour their budgets into maintaining basic operations rather than funding innovation. Embedding AI across your organization requires you to shift priorities to:
• AI R&D and leading-edge projects to stay ahead of competitors.
• Talent acquisition & development - upskilling their teams to partner with AI.
• Developing AI solutions that directly drive business results.
Take McDonald’s, for example. They’ve integrated AI into their operations to streamline efficiency and improve customer experience. With their acquisition of Dynamic Yield, they brought AI-driven personalization to their drive-thrus, offering recommendations based on time of day, weather, and customer preferences. They’ve also used AI to fine-tune inventory management, cutting waste while ensuring popular items are always available. By integrating AI at the core of their operations, McDonald’s is serving food smarter, faster, and more efficiently—a prime example of IT transforming the business itself.
Organizations stuck in the past—dedicating most of their budgets to simply “keeping the lights on”—will fall behind in an AI-driven future.
The New Competitive Edge
AI hasn't just shifted the playing field—it’s rewritten the rules of competition entirely. Today, success depends on mastering three critical dimensions:
Value: Are your AI initiatives solving real, meaningful business problems that drive measurable outcomes, or are you falling into the trap of pursuing “shiny projects” with no strategic impact? Successful organizations focus relentlessly on initiatives tied to operational efficiency, revenue growth, and enhanced customer satisfaction. Too often, I see efforts that amount to little more than “hand waving”—giving the illusion of progress. While this may provide short-term cover, it ultimately jeopardizes the long-term success of your business.
Speed: How quickly can you move from pilot to production and see tangible results? Speed matters because AI is a game of momentum. The faster you deploy and refine your solutions, the better you position yourself to stay ahead of competitors. Agile experimentation and iterative learning—foundational principles I’ve championed—are critical here. However, speed without guardrails is a recipe for disaster! Moving too quickly without proper governance or alignment creates a myriad of risks. That’s why I emphasize the importance of "speed with rigor"—balancing urgency with discipline to ensure success at scale.
Scale: Can you take individual AI successes and expand them across your enterprise? True impact comes from embedding AI into the DNA of your organization, aligning it with strategic goals, and operationalizing it for sustainable growth. Scaling requires more than replication—it demands leadership, cultural alignment, and a clear roadmap to turn innovation into a long-term competitive advantage.
By mastering these three dimensions—value, speed with rigor, and scale—organizations can transform AI from a technological experiment into a core driver of business success.
Walmart is a great example. They’ve embraced AI to tackle meaningful business challenges, deploying it at scale across their operations. AI powers their supply chain, helping predict demand and reduce waste by optimizing inventory and delivery routes. It’s also reshaped customer experiences with AI-driven tools like intelligent shopping assistants and personalized recommendations. Walmart’s bold use of AI has not only improved efficiency but also helped them maintain a competitive edge in retail, proving the value of thinking big and moving fast.
What’s Next
AI is changing everything—faster than most companies are ready to handle. Below, I've lined out 10 predictions to help you to see what’s coming in the next five years.
IT Fully Embedded into Business Strategy: IT will no longer be viewed as a support function but will evolve into a driver of core business strategies, co-creating revenue-generating initiatives alongside business leaders. Realistically, only a minority of companies will achieve this transformation within the next five years, but those that do will gain a massive competitive edge. By the following five years, organizations that fail to make this shift will face obsolescence.
The Rise of Chief AI Officers and AI-Specific Roles: AI will require dedicated leadership at the executive level, with roles like Chief AI Officers and AI Strategists ensuring organizations maximize AI’s value while managing risks. Not every company will need a CAIO, but all will require a clear owner for identifying AI opportunities and mitigating risks.
SMBs and Startups Disrupting Industry Giants: Armed with affordable AI tools, small and midsize businesses will outmaneuver slower competitors by identifying niche opportunities and leveraging their agility. Expect to see billion-dollar companies with fewer than 20 employees become commonplace, reshaping traditional perceptions of what defines scale.
Enterprise-Startup Symbiosis: Large companies and startups will form mutually beneficial partnerships, with startups delivering cutting-edge AI innovation and enterprises providing the scale, capital, and infrastructure needed for widespread adoption. This model is already emerging in the tech sector and will continue to proliferate across industries.
AI as the Driver of New Business Models: Companies will move beyond using AI to optimize internal operations and start leveraging it to create entirely new revenue streams. Internal AI systems will become commercial platforms, offering services like predictive analytics, automation-as-a-service, or AI-tailored solutions for external clients. Creating communities around these AI-driven products and services will be a key differentiator. Businesses that successfully commercialize their AI capabilities will unlock innovative pathways for growth and redefine their competitive positions.
The Innovation Gap Will Widen—Quickly: The pace of AI-driven innovation will divide industries into leaders and laggards. Companies that effectively scale AI will accelerate rapidly, leaving those stuck in outdated models struggling to keep up. This gap will not just be technological; it will manifest in customer experience, operational efficiency, and overall market relevance.
AI Reshaping Workforce Dynamics: Hybrid roles blending technical and business expertise—like AI Product Managers and Business-Technology Strategists—will become essential. Many companies will initially over-automate, leading to customer dissatisfaction and compliance issues, before realizing that the real power lies in upskilling employees to partner with AI rather than replacing them. There’s so much to unpack here—because this transition won’t be smooth. Individual job roles will experience significant disruption, with some being redefined entirely and others disappearing altogether.
Cultural Transformations Driven by AI Adoption: Organizations fostering cultures of experimentation, iterative learning, and cross-functional collaboration will thrive. Those clinging to rigid hierarchies and traditional decision-making processes will stagnate, unable to adapt to the speed and demands of an AI-driven world. Start small, test, learn, iterate, scale.
AI Governance as a Competitive Differentiator: Companies with robust AI governance frameworks and a commitment to transparency will gain a significant edge. Earning trust from customers, regulators, and investors will become a critical competitive advantage as scrutiny over AI usage intensifies.
Innovation Growth/Death from AI Access Democratization: Over the last 2 years, affordable and accessible AI tools have empowered businesses of all sizes, breaking down traditional barriers to innovation. My own small business and stealth startup have benefitted tremendously from this reality. I am now deeply concerned about the impacts of pending legal and regulatory decisions in this space. Democratization of access to generative AI has been fueled by organizations using broadly scraped intellectual property to train models, without compensation. If regulations curtail this practice, control will revert to a handful of tech giants, whose profit-driven priorities will stifle innovation and limit access. Remember—big companies benefit from regulation. The democratized access AI ecosystem that we’ve come to rely upon could be dismantled—essentially overnight—leaving us once again at the mercy of a few Goliath firms.
The key takeaway here is that companies stuck in the “old school” approach will struggle to keep up. And the ones that don’t change? They risk becoming irrelevant.
How to Move Ahead
If you’re ready to move beyond outdated models and fully embrace an AI-driven future, here’s how to position your organization for success:
Audit Your IT and Business Landscape for AI Opportunities: Start with a clear-eyed review of your operations. Where can AI deliver measurable results? Focus on areas where AI can solve real problems, improve efficiency, or create new revenue streams. Avoid getting bogged down in writing endless policies or chasing “shiny” projects that lack strategic alignment or clear impact. And for heaven’s sake, stop with the hand-waving tactics—roll up your sleeves and DO THE HARD WORK that drives real outcomes!
Invest in Hybrid Talent: Focus on building roles that blend technical and business expertise, such as AI Product Managers and Business-Technology Strategists. These roles are critical for turning AI’s potential into practical, profitable outcomes. Look for individuals with natural strengths and characteristics suited to these positions—I’ve explored this in a prior blog.
At the same time, prioritize upskilling your existing workforce to collaborate effectively with AI. Human+AI partnerships are essential to creating sustained value. For hiring managers, I encourage you to rethink outdated criteria. Stop focusing exclusively on enterprise experience and instead seek out candidates with entrepreneurial backgrounds—people who bring creativity, agility, and a bias toward action. Don’t overlook niche consultancies either; they often bring specialized expertise and fresh perspectives. These qualities are indispensable for driving innovation and building AI-powered solutions.
Shift IT from Support to Strategic Partner: IT should no longer be viewed as a cost center. Elevate IT leaders to co-own business outcomes and drive revenue-generating initiatives. For example, challenge IT to lead the creation of a new external product or service, such as transforming an internal system into a platform that generates revenue or creating an industry specific AI solution. If your company needs this capability, others likely do, too! To make this happen, seek out and empower your intrapreneurs—those within your organization who combine technical expertise with entrepreneurial vision.
Fund AI Projects with Clear ROI: Dedicate resources to initiatives that are directly aligned with business goals, such as cost savings, revenue growth, or improving customer experiences. Begin with small, measurable pilots to demonstrate value, then refine and scale for greater impact. Treat AI investments like your R&D budget—focused on experimentation and innovation. This is not traditional IT!
Move Fast, but with Accountability: Speed is critical in AI, but moving too quickly without clear guardrails can lead to missteps that harm your business. Implement strong accountability frameworks, ensure transparency, and establish measurable performance benchmarks to keep projects on track while mitigating risks. This is what I call “speed with rigor”—balancing urgency with precision to drive sustainable results.
The Bottom Line
IT no longer supports the business—IT is the business. Organizations that recognize this shift and position IT as a strategic driver of innovation, growth, and value creation will lead the way in the AI-driven future. Those that fail to adapt, clinging to outdated mindsets and silos, will find themselves increasingly irrelevant.
Transform yourself before the market does it for you. Embrace AI confidently, hold IT responsible for results, and you'll prepare your organization for long-term success.