Rohan Sharma | Author, “AI and the Boardroom” | Data & Analytics Leader at Mattel.
As I write this, enterprises are undergoing a massive AI-led digital transformation, and the changes we’ve been anticipating are finally taking shape. Business models and investment strategies are being transformed, and teams are being reimagined.
Companies that didn’t exist 24 months ago are gaining market share, and new revenue streams are opening as the tech stack is being redesigned. At the same time, many of the SaaS, fintech and other categories that reported massive growth in the last five years are starting to slow down dramatically. Everything from search to SaaS pricing is being re-imagined.
In this new world, four distinct themes are emerging as the AI-led digital transformation takes hold:
1. The CIO’s moment has arrived, again.
CIOs have emerged as the new power centers for AI budgets, taking center stage in boardrooms globally and transcending their traditional roles.
For the last decade, the SaaS business model dominated the landscape. Business leaders in sales, HR, finance and marketing controlled budgets and efficiency initiatives. They worked directly with SaaS vendors such as Workday, Salesforce, Adobe Creative Cloud, etc., often sidestepping CIOs, and as a result, SaaS vendors learned to target these business leaders, following the money and decision-making power.
Now, AI has upended this model. Many boards now task CIOs with delivering the company’s AI vision. They seek a full architectural shift led by AI, not just point solutions.
CIOs no longer simply manage IT infrastructure, cybersecurity or allocate capital to software solutions. They have started to drive AI strategy and are making key decisions in major business initiatives. As a result of newly found visibility, many CIOs are rewriting budgets, reallocating resources from traditional SaaS subscriptions to AI initiatives, and building teams of data scientists and AI specialists.
In my view, this shift will continue to accelerate. I predict that within the next three years, we’ll see CIOs regularly appointed to company boards, reflecting their critical role in shaping business strategy.
Key takeaway: Companies should reevaluate their C-suite structure to ensure CIOs have the authority and resources needed to drive AI-led transformation.
2. Companies are reimagining AI architecture.
Companies, particularly early adopters, had their ear to the ground last year on evolving AI architecture—in 2024, most front runners are starting to build it as we speak. While variations exist, I’ve noticed a three-layer AI stack is taking shape and being implemented in real time:
1. Scalable, cloud data lake
2. Foundational model as a service
3. Generative AI applications
CIOs who suddenly found themselves in charge of executing this shift are rapidly assembling teams of data scientists, data engineers, AI engineers and solution architects.
As CIOs launch proof-of-concept projects demonstrating AI’s value, they also face a simultaneous immediate pressure to scale. This need for scaling demands a newly reimagined tech stack, giving rise to the new AI architecture.
Looking ahead, I anticipate that in the next three years, we’ll see the emergence of industry-specific AI architectures. For instance, healthcare might develop specialized data lakes and models tailored to patient care and drug discovery, while finance could create architectures optimized for risk assessment and fraud detection.
Key takeaway: Start building your AI architecture now, but design it with flexibility in mind to adapt to rapid innovation and emerging industry standards in the AI space.
3. Organizational structures and headcounts are changing.
As AI-led digital transformation takes hold, a third critical theme is emerging: fundamental changes in how organizations invest in headcount.
In my conversations with CIOs and VPs, I’ve noticed a clear trend: Many companies are not increasing their aggregate expenditures, and their earnings reports confirm this. Instead, as CIO-led centralized AI initiatives grow, budgets for other priorities are being squeezed. In my discussions with leaders across major retail, life sciences and e-commerce giants worldwide, some common areas of organizational impact are evident:
• Headcount re-organization: Automation is driving efficiency, leading to headcount reductions in traditional, non-AI roles. Simultaneously, AI-focused companies are expanding their teams with talent to support AI initiatives but cutting headcount in non-AI programs. I’ve noticed this trend is global, seen in companies across the U.S., Europe, South America and beyond.
• SaaS investment and pricing model shift: The era of per-seat SaaS pricing is ending. Companies are reevaluating their SaaS investments, looking for AI-driven alternatives that offer more value and efficiency. As a result, many SaaS companies are quickly pivoting their pricing strategies to defend their territory.
Key takeaway: Conduct a thorough audit of your organizational structure and invest in reskilling programs to prepare your workforce for an AI-driven future.
4. AI Governance, operating models and change management are becoming key.
Companies are realizing the need for robust AI governance as a necessity. Most CIOs I speak to at summits are scrambling to establish some version of AI centers of excellence (CoE), AI governance committees, AI guardrails or governance frameworks. In addition, companies seeing success with their AI pilots and early investments have realized that the human element and effective change management is crucial to AI adoption.
Another clear trend that emerged after a fireside chat with 20 CIOs recently was that companies with clear, well-defined outcomes from their pilots and early initiatives, dedicated AI teams and cross-functional collaboration are pulling ahead, while those without are struggling to keep pace.
Key takeaway: Companies need to establish well laid out governance framework, clear outcomes from their pilots, cross-functional buy-in and collaboration and effective change management.
The future is now.
As I conclude this look at the seismic shift of the AI landscape, one thing is clear: The future we’ve been preparing for is here. The companies succeeding right now are those that recognized this shift early and acted decisively.
They also realized early on that AI adoption isn’t just about technology—it’s about reimagining every aspect of how we do business.
Growth in this new era will require continuous learning, adaptability and a willingness to challenge long-held assumptions about how organizations should operate. The excitement is palpable, the opportunities are immense, and the time to act is now. Are you ready?
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