Finnish and Nordic leaders must rethink AI strategy in 2026

Why it matters

Your responsibility is sustaining long-term value and strengthening resilience. AI oversight is now central and the progress is evident: 31 percent of boards lack AI on agendas (down from 45 percent). Sixty-six percent have limited knowledge (down from 79 percent). Thirty-three percent are unsatisfied with time spent (down from 46 percent). But progress isn’t enough specially in the Nordics, where the AI literacy of boards is reported to be lower than global average. AI advancement is accelerating and the gap between board knowledge and governance complexity is widening.

Chairs need to ensure the board has appropriate knowledge and experience for effective oversight. Challenge management on human-centric vs. Tech-centric approaches as Tech-centric approaches are 1.6 times more likely to fail. Oversee the three tipping points to ensure your organization builds trust and manages cultural debt.

What it means for your role

Boards need to understand their organization’s AI maturity and strategy and evaluate key questions: Does management have the right human-centric adoption strategy? Or are we tech-centric? Does management have comprehensive strategy considering resources, capital, pace, metrics, vendors, and trends? Does the board understand risks and opportunities?

Deloitte’s board report demonstrate that boards are unhappy with the adoption pace of AI with over 50% of organisations feeling the need to accelerate as only 25% are satisfied. Most important, boards should challenge whether management moves fast enough while avoiding a heavy tech-centric only approach. Also, boards should be confident to understand risk evaluation, including risks of not using AI.

Boards should also be bold to recognise fragilities in its own composition. Are boards’ structure or composition changes necessary? Does the board have appropriate experience for oversight and right levels of knowledge? EU AI Act forces those adopting, deploying, managing AI to acquire AI Literacy. What exactly literacy means is blurry despite mandatory.

It’s up to boards to remain engaged in this evolving landscape building legitimacy to ask: Does the management understand the areas where AI will have most critical impact in the company or in its business environment?

How you can act

Assess board AI knowledge and experience: Conduct skills inventory. Consider whether composition needs adjustment. Establish regular AI education cadence and advisory sessions. Deloitte has been visiting board rooms in Finland to support literacy, for example.

Establish clear oversight framework and determine necessary board structure changes: Ensure you understand executive responsibility and reporting, observing and establishing metrics measuring whether AI contributes to strategic goals.

Challenge management on human-centric vs. Tech-centric approaches: Ask whether your organization intentionally designs human-AI interactions or simply layers AI onto systems. Understand orchestration progress and assess cultural debt management.

Ensure trust and responsible risk management: Understand how your organization addresses workforce data quality decline and assess governance frameworks incorporating Trustworthy AI, fairness, equity, and bias mitigation. Boards should ensure AI strategy aligns with talent and financial strategies.

Stay engaged and curious: The AI landscape evolves rapidly, and the EU AI Act is coming into force. Ensure your board remains actively engaged, learning, asking right questions, challenging constructively, and positioning for success.

Why it matters

Your role has fundamentally changed. You’re architecting a transformation that touches every aspect of how your organization creates value. Organizations taking a tech-focused approach are 1.6 times more likely to fail compared to those taking a human-centric approach.

Three tipping points demand your attention. First, the boundary between humans and machines is blurring. You must move beyond side-by-side work to designing intentional human-machine synergy. Second, relentless cost-cutting is giving way to value creation. Human capacity is becoming scarce; organizations that channel efficiency gains into reinvestment will thrive. Third, static planning is obsolete. Strategy and execution are merging; you must orchestrate people, skills, data, and technology in real time.

What it means for your role

You have three critical roles. First, you’re the dealmaker-in-chief securing computing power. The market for specialized AI chips will reach $120 billion by 2027. Engage directly with hardware companies and align your CIO on procurement strategies.

Second, you’re the venture capitalist calibrating AI ambition. Decide whether your organization will be a first mover building custom language models or a fast follower. This shapes your data strategy and competitive positioning.

Third, you’re the champion establishing AI centres of excellence. Your role is to champion their establishment, ensure critical elements are funded, and win stakeholder hearts and minds. Champion a clear purpose: supercharging human capability, not replacing humans.

How you can act

Make key strategic decisions upfront: Will you focus on a few AI choices or maximize optionality? How will you build flexibility? How will you measure costs and performance? How will you embed trust and guardrails? These decisions prevent technical sprawl.

Engage directly with your CFO and CIO on the three tipping points: Ensure financial strategy supports value creation, technology strategy prioritizes human-centric adoption, and your CHRO leads cultural transformation.

Establish metrics beyond technology deployment: Measure intentional human-AI interaction design. Track orchestration progress and monitor cultural evolution. Organizations cultivating adaptive approaches are 2.4 times more likely to report better financial results.

Why it matters

Your mandate is expanding. More than half of CFOs now influence enterprise strategy, handling 20 percent more responsibilities than peers. But you face a critical challenge: navigating the tension between cost efficiency and workforce value creation.

For years, cost pressures pushed organizations toward efficiency at all costs. That model is tipping. Organizations that channel efficiency gains into reinvestment fuel new value creation and worker performance. While AI drives cost savings, real competitive advantage comes from using those savings to invest in innovation and human capability.

Organizations prioritizing work design and intentional human-machine redesign are twice as likely to exceed AI ROI expectations, yet only 6 percent are leading in this area. This gap represents both risk and opportunity.

What it means for your role

Your 2026 priorities are clear: planning for external challenges, adopting technological capabilities, developing new products, optimizing capital allocation, and protecting resources through discipline. But these aren’t separate—they’re interconnected.

Workforce costs must shift from line items to be minimized to strategic investments in human capability. Measure workforce investment against value creation, not just cost reduction, and as human capacity is scarce, cfos should invest where humans create unique value.

Together with your CHRO, you should define what “value” means in workforce transformation and ensure talent analytics inform financial planning. Align on metrics measuring on both business and human outcomes and resist treating AI purely as a cost-reduction tool.

Your relationship with your CIO matters equally. Ensure technology investments deliver measurable value. The data shows 63 percent of finance leaders actively use AI, but only 21 percent see clear, measurable value. This gap suggests many organizations deploy AI without financial discipline.

How you can act

Mandate a connected data infrastructure: Bring previously disconnected data together to enable better scenario planning and capital allocation. Leading organizations run sophisticated scenario models daily, combining pricing, inventory, supplier, and customer data.

Treat cost management as continuous, strategic discipline: Invest in dedicated expense teams that leverage finops, tokenization framework, and cloud solutions: 51 percent of cost management owners deploy them. Use AI to identify opportunities and establish finops rigor around cost metrics.

Develop holistic AI ROI views. Don’t measure success purely in cost savings but also by measuring intentional human-AI interaction design. Organizations cultivating adaptive approaches are 2.4 times more likely to report better financial results.

Align financial strategy with CEO vision and CHRO workforce strategy: Ensure capital allocation supports human-centric AI adoption and keep CIO partnership for AI (apis, Tokens, Cloud) costs projections understandable and predictable. Ensure that the costs are related to value generated to your company and connected to defined ROI. When realising efficiency gains, reinvest them in innovation and capability development.

Why it matters

Your role is at an inflection point. As AI rises to CEO and board priorities, you’re asked to deliver more while constrained by structures you’re meant to transform. Cios are expected to embed AI across the enterprise—often within legacy environments and without proportional funding—while sustaining everything you own.

This challenge isn’t technological; it’s organizational. According to Deloitte’s Global Technology Leadership Study 2026³, CIOs have now a dual mandate: They are required to go deep in the technology, especially AI, while leading the enterprise’s AI transformation along a fragmented technology leadership.

Three constraints limit your ability to translate AI ambition into execution. First, structural fragmentation: 71 percent of organizations have five or more C-suite tech leaders. Second, misaligned funding: 89 percent allocate no more than 25 percent of budgets to AI. Third, outdated operating models: 81 percent are confident their current model can deploy AI, yet 75 percent must change it within 12-18 months.

What it means for your role

Your top priorities are clear: build AI-fluent teams, lead enterprise AI adoption and governance, and strengthen cybersecurity and resilience. But these must be integrated, not siloed.

This requires the “dual mandate”: pairing deep technical expertise with the ability to drive enterprise outcomes. Technical depth is baseline as you must understand AI architecture, governance, cybersecurity, and emerging technologies. Next you must mobilize stakeholders, drive adoption, manage trade-offs, and translate ambition into measurable business value.

Your role is to ensure that the organisation leads in intentional human-AI interaction design, enhancing human capabilities and not replacing it. Organisations are 2.5 times more likely to report better financial results when that is considered. This requires cios to close collaborate with chros on governance, decision rights, and cultural implications.

How you can act

Anticipate and shape what AI changes next: Look beyond immediate use cases to address second-order impacts on architecture, talent, governance, and capital allocation. Treat AI as integrative, not additive.

Make hard technology trade-offs: Apply disciplined judgment to translate ambition into a focused portfolio with clear value cases, defined risk posture, and explicit time horizons. Be transparent on trade-offs and communicate them in enterprise terms.

Navigate risk without stalling progress: Advance AI while managing risk, compliance, and security. Success depends on bringing stakeholders along early and balancing speed with responsible operation.

You are partnering with business leaders to redesign how their work gets done: Orchestrate CEO, CFO, CHRO, and business leaders to drive prioritization and align around shared outcomes. AI success is organizational accountability, not just tech leadership.

Make AI an enterprise muscle, not an IT project: Embed it into core platforms and processes, help to redesign legacy workflows considering hybrid workforce and how work gest done. Build repeatable capabilities that scale AI while sustaining operational excellence and resilience.

Why it matters

You stand at the centre of the most critical transformation your organization will undertake and the data is clear: tech-focused approaches are 1.6 times more likely to fail, but organizations leading in intentional human-AI interaction design are 2.5 times more likely to report better financial results. Organizations cultivating adaptive approaches are 2.4 times more likely to report better results and provide meaningful work. Yet only 6 percent lead in human-AI interaction design. Finally, only 7 percent make great progress in orchestrating people, skills, data, and technology, and just 5 percent manage AI’s cultural impact well.

These gaps represent crisis and an opportunity to act. Most organizations implement AI without intentionally designing human-machine interaction, orchestrating effectively, or addressing cultural implications. By stepping into this space, you can differentiate your organization.

What it means for your role

Your role sits at the intersection of three critical transformations. CHROs should design human-AI interactions; address the cultural debt in ways you weren’t tasked before; and to deliver a learning architecture that enables continuous adaptation. All of them will require you to act as a true orchestrator.

When comes to design of human-AI interactions, you are expected to address not just the organizational level, but at the granular level where work actually happens. This is fundamentally different from traditional HR work. It’s not a simple adoption of a tool; it is a redesigning the nature of human work. The question is "what does collaboration between humans and machines look like in this specific role, this specific workflow, this specific decision?" - That requires you to understand and define interaction types: “AI as boss, coach, collaborator, assistant, liaison”, and recognize that different work demands different relationships between humans and machines.

Next, cultural debt is the accumulation of negative consequences from neglecting the human and ethical dimensions of technology. The data reveals that 42 percent of workers say their organizations rarely evaluate AI's impact on culture and values. Eighty percent worry that colleagues use AI to appear more productive rather than to do better work. Only 5 percent of organizations manage this well. This is a fundamental misalignment between how organizations are deploying AI and what their people actually value. You're responsible for surfacing and addressing that misalignment.

The third critical transformation is about owning the learning architecture that enables continuous adaptation. In a world where AI is evolving faster than organizations can plan, the traditional change management cycle —beginning, middle and end— is obsolete. You must embed continuous and tailored learning into the flow of work itself and the roles performing them. This requires a different approach to how you think about capability building and organizational adaptation.

These three critical transformations demand you to act as a champion of orchestration. It’s fundamental to demonstrate ability to fluidly reconfigure people, skills, data, and technology in real time as conditions shift. This moves you from workforce planning (a static, annual exercise) to workforce orchestration (a continuous, dynamic capability). Organizations that lead in orchestration are twice as likely to report better financial results. Yet only 7 percent make great progress.

The implication for your role is profound: you can no longer think in terms of fixed job structures, career ladders, and annual planning cycles. You must think in terms of fluid teams, mission-driven configurations, and continuous reallocation of capability.

How you can act

Establish cross-functional governance for human-AI collaboration: Work with your CIO to define design principles such as outcome-driven, contextual, transparent, adaptive, human-centred, empowering. Establish clear decision rights.

Launch cultural assessment and evolution: Evaluate AI’s impact on culture, trust, and connection. Address concerns accumulating as cultural debt and reinforce purpose and values. Design interventions encouraging human connection.

Redesign workforce planning to support orchestration: Move beyond static job descriptions to fluid roles where human-machine collaboration is considered when planning workforce size. Explore “agentic” strategies and cross-functional leadership models.

Embed continuous learning in work: Create omnichannel experiences surrounding workers with adaptive experiences. Shift to hyper-personalized learning and create continuous feedback loops.

Align workforce strategy with CEO vision and CFO financial strategy: Ensure talent investments support human-centric adoption. Invest where humans create unique value and establish metrics measuring both business and human outcomes.