Are you maximising value from AI?
Artificial Intelligence (AI) adoption is accelerating across industries, with organisations investing in tools, platforms, and skilled teams to stay competitive. The goal is to drive innovation, improve efficiency, and deliver measurable outcomes. Further derivatives of AI are becoming more accessible for companies to leverage, with Agentic AI leading the charge[1] as generative AI use is now business as usual to most.
Despite this momentum, the main challenge we hear being asked by boards is if they are "innovating fast enough to keep up with the competition and emerging disruptors”. Governance is seen as a barrier for AI deployers, and with several industry frameworks and standards now available, which are the best for measures of success, innovation, and return on investment?
Foundational challenges – such as poor data quality, limited governance, and skills shortages – often prevent AI from scaling effectively. Here, we explore how to build strong AI foundations and ask the question: are you leveraging AI fast enough, and to its fullest extent?
What’s really holding back AI innovation?
Without a clear strategy to scale AI across the business, initiatives often remain isolated within individual teams or departments, limiting the overall impact.
The most common blockers or reasons for failure of AI pilots are fragmented data, legacy systems, and unclear ownership. Without high-quality, well-governed data, AI models produce unreliable outputs, undermining trust and scalability. Inconsistent data lineage and lack of transparency also expose firms to privacy breaches and compliance risks.
Meanwhile, AI literacy remains low. Many employees lack the skills to interpret, challenge, or responsibly use AI-generated outputs. This limits adoption and increases the risk of misuse, especially with open-source tools or shadow AI deployments. Even where governance frameworks exist, they often fail to reach frontline teams or third-party vendors, leaving gaps in oversight.
In short, governance isn’t the bottleneck, it’s the lack of effective data governance and AI literacy that’s holding companies back. Addressing these gaps is now essential to unlock AI’s full potential.
Building strong AI foundations
What’s changing the status quo is the growing pressure to demonstrate ROI. Business leaders are demanding measurable outcomes, not just innovation theatre. This shift is forcing organisations to rethink their foundations—investing in data quality, cross-functional training, and scalable governance that enables, rather than restricts, innovation. But the challenge can be finding the right area to focus efforts.
A structured, trusted approach to assess AI readiness, mitigate risks, and unlock AI’s full potential is needed.
By strengthening these foundational elements, organisations position themselves to scale AI with confidence. They can move faster, adapt more easily, and realise the full value of intelligent technologies.
Practical steps: How to accelerate AI maturity
Establish a strategic AI vision
Align AI initiatives with business strategy, clearly defining target outcomes, value levers, and responsible AI principles. Secure board level sponsorship to embed AI in the corporate agenda.
Assess current AI maturity & gaps
Use a structured AI maturity assessment to evaluate people, process, technology, and governance capabilities. Identify gaps that hinder scalability and innovation.
Build an AI governance framework
Implement policies, risk controls, and compliance processes (e.g., bias testing, explainability, regulatory alignment) that work for your business, to ensure safe, ethical, and trusted AI deployment.
Invest in scalable infrastructure & tools
Adopt cloud, MLOps, and reusable AI components to accelerate model deployment, monitoring, and iteration.
Develop AI skills & culture
Launch targeted upskilling programmes, cross-functional teams, and innovation sandboxes to promote AI experimentation.
Measure, iterate, and scale
Track ROI, performance, and adoption metrics, refining models and approaches based on feedback to scale high-impact use cases.
Unlocking the full value of AI
Companies are investing heavily in AI, yet many struggle to realise its full value. The biggest barriers are no longer regulatory constraints or governance frameworks themselves—but rather poor data governance and low AI literacy across the organisation.
To further discuss how to accelerate your AI maturity and unlock its full value, get in touch with Alex Hunt, Data Services Leader for Large Corporates at Grant Thornton.
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[1] Gartner Hype Cycle Identifies Top AI Innovations in 2025
