By Anshuman Sengar- Partner, Kearney & Bianca Eden- Consultant, Kearney
Undeniable and unstoppable – AI is forging a new economic reality.
In the past four weeks alone, over $200B in AI-related investments have been announced. More than 20 LLMs are being launched each month, and five of the world’s ten most valuable companies (by market capitalisation) are pivoting to make AI the foundation of their businesses.
This might feel like a “one-small-step-for-man-one-giant-leap-for-mankind” moment. However, not every business needs to rush to the launchpad. AI opportunities differ vastly across industries, and success comes from setting the right pace and approach for your organisation.
Whatever your strategy, there are five imperatives for 2025.
1. Harness the opportunity in agentic AI with strategic deployment
The AI landscape is changing again, and the next frontier is agentic AI.
Unlike GenAI which waits for prompts, Agentic AI takes initiative – autonomously gathering information, evaluating options, and executing decisions to achieve defined goals. This leap represents a fundamental shift from reactive to proactive intelligence.
Agentic AI orchestrates multiple ‘agents’ – tools, databases, and other systems – with minimal human oversight. This autonomy unlocks new dimensions of productivity and scale but introduces greater complexity and risk. Like GenAI, it is probabilistic with occasional errors; unlike GenAI, it acts on outputs, meaning small errors can escalate into significant risks.
Strategic deployment is key. Organisations should begin with controlled, lower stakes use cases where errors are tolerable, learning is rapid, and buy-in is strong. Areas like IT service desks, cyber threat detection and supply chain management are a good starting point. For example, Agentforce can build service agents that handle most tasks needed to resolve an IT service ticket, improving response times and freeing teams for more strategic work.
These advancements will not slow down – invest carefully in the way that is right for your business.
2. Prioritise rigorously and link investments to sources of competitive advantage
Global companies are already investing ~25% of their data and analytics budgets into GenAI. However, with only 18% of Fortune 1000 executives reporting a ‘high degree’ of business value from AI, many organisations are struggling to prove their journey isn’t all hype and no landing.
To invest in the right initiatives, companies must take a holistic view of the value chain. The key is understanding where your competitive advantage lies – not just now but in five, ten years – and ruthlessly prioritising investments in areas that deliver the most impact.
For insurers, this might mean transforming risk models; for miners, exploration is where the gold lies. Different industries, same principle: invest where it matters the most.
Even with laser-sharp focus, evaluating ROI can feel like an impossible mission, fraught with hidden costs. Data quality and model governance are often underestimated. True ROI requires accounting of every line item: data preparation, development, training, testing, integration, infrastructure, monitoring, governance, human expertise and change management.
Prioritise and invest smartly to avoid getting lost in the black hole of unchecked costs – the goal is not just lift-off, but long-term, measurable gains.
3. Invest in talent and partner strategically
The industrial revolution redefined human roles, replacing manual labour with machines and creating a need for new skills – designing, operating, and managing systems that powered progress.
In 2025, we stand at a similar inflection point. AI isn’t replacing people – it’s transforming how people add value in an AI-powered world. The skills of the future will combine specialised functional knowledge with critical thinking and the ability to evaluate technical, commercial, compliance and ethical factors in the AI tools we buy, build, manage and use.
This shift is redefining roles and organisations need a fit-for-purpose talent strategy to manage the transition. The challenge? Today, just 9% of the workforce has strong AI proficiency – in finance and HR, it’s as low as 5%. Even in the C-Suite, proficiency is just 12%.
Three immediate steps will help organisations address this challenge:
– Appoint top AI talent to your Board: their strategic approach and knowledge of the technology will support better investments and governance decisions;
– Develop future AI leaders: Nurture a pipeline of high-potential talent with the technical skills and executive presence to guide AI initiatives;
– Partner strategically: Outsource where commoditised products like LLMs can ease the talent-gap burden.
4. Uplift governance to comply with regulation and mitigate AI risks
Last year, an astonishing 97% of executives from 1500 leading organisations reported GenAI related security breaches. Meanwhile, concerns around bias, inaccuracy and misuse persist, driving new and evolved regulation.
AI risks and impacts don’t fit neatly into traditional risk management frameworks, often exposing differing risk appetites among Boards, CIOs, and business leaders. Aligning on risk/reward appetite, and acceptable impacts – particularly for customers and employees – requires a level of nuance that goes beyond the standard risk management approach.
Trust is fragile and the stakes are high. The “pub test” offers a simple litmus test: if your AI use case made front-page news, what would public sentiment be? If the answer leans negative, you’re on risky ground.
To govern AI effectively, organisations must align Board, executives, and senior management on a shared AI governance framework that defines your boundaries for AI use, and the impacts you will and won’t tolerate – responsive to regulation. Uplift policies, structures, and practices to embed accountability and safeguard brand value and trust.
AI governance isn’t a back-office function, it is a strategic imperative. The organisations that get it right will lead with customer trust, operational resilience, and sustained value.
5. Build a culture of agility and learning
Tech giants like Google, Meta and Salesforce are rapidly embedding AI into their roadmaps, transforming the tools and platforms businesses rely on. Even if your organisation isn’t ready, the technology you use is evolving and the pace of change will affect you.
This isn’t just a technology shift, it’s a human one. The organisations that thrive will be those that are able to adapt swiftly and bring their people along for the journey.
91% of Fortune 1000 companies report cultural resistance as the greatest barrier to unlocking value from data and AI, yet it’s key to navigating AI’s disruption.
Three priorities will build AI agility:
- Embed AI strategy in enterprise strategy: be hyper-focused in aligning AI initiatives with enterprise priorities;
- Align on common objectives: take an enterprise view on AI deployment and align leadership on common objectives;
- Adopt a learning mindset: cultivate curiosity and make it safe to make (and learn from) mistakes.
AI is here to stay and whether you chose to leap forward or play the waiting game, be intentional in your decisions, targeted in your investments and active in your learning.