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Home Market Research Market Analysis

From Hype To Scalable Impact

by TheAdviserMagazine
2 months ago
in Market Analysis
Reading Time: 3 mins read
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From Hype To Scalable Impact
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Artificial intelligence has moved from the margins to the mainstream. But as the buzz around generative and agentic AI intensifies, many organizations are asking a more grounded question: How do we move from experimentation to enterprise-scale impact?

Last Tuesday, my colleagues Indranil Bandyopadhyay and Raluca Alexandru hosted a virtual event for data and AI leaders focused on these topics. We found that while most organizations claim to have documented AI and data strategies, few have activated them in ways that drive measurable business outcomes. The gap between strategy and execution is widening — and closing it requires more than technology.

Activate Your AI Strategy For Business Impact

According to Forrester’s Data And Analytics Survey, 2025, 69% of organizations say they have a data strategy and 66% report having an AI strategy. Yet many of these are disconnected from business priorities. A successful AI strategy isn’t just a document — it’s a living framework that aligns outcomes, capabilities, and risk.

Activation means embedding AI into decision-making processes, defining clear ownership, and ensuring that strategy evolves alongside emerging technologies and shifting risk appetites.

Business Ownership Drives AI Value

While technology teams often lead AI efforts, business stakeholders must define the problems that AI is solving. Without this alignment, AI risks becoming a technical exercise rather than a transformative force. Cross-functional governance — bringing together legal, compliance, HR, and business units — is critical to ensure that AI initiatives are viable, valuable, and scalable.

Organizations that succeed treat AI as a business strategy, not just a tech investment. They build adaptive cultures, foster data literacy, and prioritize use cases that deliver tangible outcomes.

Prioritize AI Use Cases To Scale Effectively

One of the biggest barriers to scaling AI is use case sprawl. Enterprises often have dozens of pilots but lack a framework to prioritize and activate them. A structured approach — sourcing ideas from across the organization, forecasting impact, prototyping with governance in mind, and iterating based on ROI and feasibility — is essential.

The most successful organizations balance experimentation with discipline. They focus on repeatable patterns, low-risk opportunities, and use cases that align with strategic goals.

AI Governance: Foundation For Trust And Growth

AI governance is often misunderstood as a blocker. In reality, it’s the foundation for trust, scalability, and compliance. There’s no one size that fits all, with some organizations gravitating more toward defensive governance (focused on risk, privacy, and control) while others, with perhaps a higher risk appetite, will embrace more offensive governance (focused on enablement, reuse, and innovation).

A “minimum viable AI governance” stack can be implemented in just 90 days. This includes:

Defining AI policy and risk levels.
Creating a use-case intake process.
Establishing data product contracts.
Documenting models and prompts.
Identifying human-in-the-loop checkpoints.
Vetting vendors for AI standards.

These foundational elements preserve trust while maintaining momentum.

Boost AI Literacy For Enterprise Adoption

Forrester’s Future Of Work Survey, 2024, shows that more than half of employees have low AIQ — limited understanding, confidence, and ethical awareness around AI. Without addressing this, adoption slows and trust erodes. Building AIQ across the organization is essential, not just through training but by fostering a culture of responsible experimentation.

AI success depends on people as much as technology. Clear roles — such as AI governance leads, data product owners, model owners, and citizen stewards — ensure accountability and turn governance from theory into practice.

Strategic AI Readiness: Turning Hype Into Impact

Strategic AI readiness isn’t about chasing the latest tech — it’s about building the foundations to scale responsibly. That means aligning strategy with business value, embedding governance early, and empowering people across the organization.

Organizations that start small, scale smart, and embed governance by design will be best positioned to turn AI hype into lasting impact. You can accelerate your efforts by leveraging Forrester’s latest research on AI strategy, governance, and use case prioritization. Please also join us at our annual Technology & Innovation Summit EMEA in London, October 8–10, where we will dive deeper into some of these themes.



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