The ability to move between academic research, business consulting work and startup creation represents a rare skill that most leaders do not possess. Professor Andy Pardoe is one name among them. His professional journey began inside some of the world’s largest consulting environments, where exposure to complex, cross-industry transformations sharpened his view of AI’s promise, and its limitations.
Organizations that lack AI leadership resources face challenges equal to those faced by organizations that have no desire to achieve their goals by using artificial intelligence. Informed AI was founded by him because he wanted to establish an organization that would provide AI leadership to companies which do not belong to the largest corporations. Today he is the Founder & Head of AI Practice.
He and his team supports AI companies which are developing their business through his advisory work and venture investments and their critical growth stages. He uses AI as a basic organizational capability which requires implementation through his people-centered approach to strategic planning. Organizations gain the ability to shape their decision-making processes and internal development through this capability.
From Consultancy to Leadership
Pardoe’s transition to consulting at one of the world’s largest firms expanded his perspective across industries but also revealed a critical gap. Small and medium-sized enterprises, along with many public companies, struggled to access AI capability without the prohibitive cost structures of the major consultancies. He founded his own firm to bridge that gap and work that evolved into Informed. AI’s current model of delivering fractional Chief AI Officer services, comprehensive consulting engagements, and executive education.
The fractional CAIO approach addresses a persistent challenge for organizations at critical inflection points. “Companies need strategic AI leadership, but not every organization can justify or sustain a full-time executive in that role. The fractional model allows us to provide that depth and continuity while scaling our engagement to match their readiness and resources.” he explains. This philosophy extends to his newest ventures which is Venture Flows VC, a dedicated SEIS fund he co-founded in 2025 to support innovative AI start-ups, and Origin Works, a growth accelerator launching this year to help later-stage companies scale commercially and expand into new markets.
Moving Beyond Proof of Concept
Organizations across industries face similar obstacles when attempting to scale AI from experimentation to enterprise-wide value creation. He identifies the pattern immediately that companies launch enthusiastic pilot projects, demonstrate proof of value, then struggle to translate those successes into sustained operational impact. His firm engages as early as possible, ideally during the proof-of concept phase, to establish foundations that support future scaling.
“We prefer to engage when organizations are still in proof of value, but we also work with firms that already have AI use cases in production. In both situations, we review what has been built and help teams understand how those early efforts must evolve,” he notes. This holistic approach examines organizational structure, culture, processes, governance, ethics, and workforce skills alongside technology. “These dimensions are often the limiting factors. Technology itself is rarely the true bottleneck. The greater challenge is the change program required to embed AI into existing workflows and decision structures,” he observes.
The Governance Imperative
Sustainable AI adoption requires enterprises to govern intelligent systems with the same rigor they apply to capital allocation and risk management. Pardoe advocates for strategy-led AI initiatives explicitly derived from business objectives, not opportunistic experimentation. “Each initiative needs a clear value thesis that maps directly to strategic goals such as margin expansion, risk reduction, or customer experience differentiation,” he emphasizes. AI use cases should function as a managed portfolio with explicit prioritization and sunset criteria comparable to investment committee discipline.
Executive ownership proves critical. A single accountable leader is often, the CEO, CIO, CDO, or CAIO that must own outcomes, not merely oversee delivery. He recommends a federated governance model balancing central standards with business unit autonomy. Enterprise-wide guardrails that define expectations for data quality, model risk, security, ethics, and compliance, while business units retain ownership of domain-specific models to ensure operational relevance. “This approach avoids two common failure modes that are either an innovative-stifling central AI team or uncontrolled shadow AI proliferating across the organization,” he explains.
Risk, ethics, and compliance must be embedded by design. AI systems require classification through risk tiering, with escalating controls for higher-impact use cases. Models must achieve explainability and auditability appropriate to their business context and regulatory requirements. He emphasizes that accountability spans the full lifecycle, noting that responsibility does not end at deployment and that ongoing monitoring for drift, bias, and unintended outcomes is mandatory for the long-term success of any AI project.
The Boardroom Challenge
Despite growing awareness, Pardoe encounters persistent misconceptions at board level. The most critical error remains viewing AI as a productivity tool rather than strategic technology. “Some boards still see AI as a copilot delivering incremental gains, rather than as transformational capability,” he observes. This perspective causes organizations to underestimate both required investment and potential value, leaving them vulnerable as competitors move more decisively.
However, momentum is building. Following ChatGPT’s release in November 2022, a growing cohort of CEOs began adopting AI more aggressively. “Already this year, we see marked shifts in boardroom attitudes, CEOs commitment is becoming more serious and increasingly backed by meaningful budget allocations. This change makes scaled, enterprise-level AI adoption achievable, not just aspirational,” he reports.
He challenges boards to evaluate AI investments beyond traditional ROI metrics. According to him, intelligent technologies represent the next frontier of human and organizational evolution, comparable in significance to the wheel or the steam engine. He emphasizes that success metrics should include organizational resilience, capability building, and long-term competitive positioning alongside financial returns. He further notes that boards should recognize AI as a long-term strategic capability and measure progress through adaptability and learning capacity. Thise will be best positioned to determine whether these investments deliver their intended impact. Firms that take this approach are much more likely to be the winners in this new era of intelligent solutions.
Balancing Innovation and Responsibility
Trustworthy & Responsible AI together with ethical considerations occupy a central position in Pardoe’s advisory framework, but he rejects the notion that governance slows innovation. “Building AI responsibly does not need to reduce velocity. It simply requires the right frameworks, tools, and processes established from the outset,” he insists. Organizations that address governance, risk, and ethical foundations early can innovate at business demanded pace without compromising accountability or trust.
He prioritizes robustness, trustworthiness, data privacy, and security as starting points for AI initiatives. He believes that these elements are not constraints on innovation. They are rather enables of.
He explains that these elements are not constraints on innovation but enablers of sustainable scale and regulatory readiness. According to him the greater challenge lies in the change program required to embed AI into processes, workflows, and decision structures. Organizations addressing this transformation holistically position themselves to balance innovation velocity with long-term accountability.
Industry Context and Strategic Flexibility
Having worked across financial services, healthcare, public services, media, and technology, Pardoe takes a nuanced view of sector-specific AI strategy. “Each organization requires an AI strategy aligned closely with its specific business and IT strategies,” he notes.
While overall structure and core focus areas remain consistent, detailed priorities, sequencing, and emphasis vary significantly by business. He also notes that AI strategy is an evolving and ever-changing set of objectives – driven by an organizations current AI maturity.
His firm often delivers strategy incrementally rather than as a single exercise, flexing both strategy and delivery model around each organization’s value drivers, operating context, and appetite for new technology. He observes that AI represents a broad and highly transformational set of capabilities. He navigates these choices while maintaining alignment with business objectives and practical constraints which is central to developing a comprehensive and effective AI strategy.
The Success Factor: Executive Sponsorship
Organizations that successfully embed AI into their operating fabric share one defining characteristic. They receive strong, visible sponsorship from the CEO. “Senior leaders must be genuinely passionate about AI’s value and understand its strategic importance,” Pardoe emphasizes. This sponsorship unlocks necessary investment levels and sustains momentum through inevitable challenges and shifting priorities.
“AI transformation is no different from other large-scale change programs. Without committed senior sponsorship and adequate budget, initiatives struggle beyond isolated successes. With them, organizations translate AI ambition into sustained, measurable enterprise impact,” he explains.
Beyond Technology: The Human Dimension
Pardoe views AI implementation as fundamentally a cultural and change challenge – focused on the people and the process. He does not see it merely as a technology deployment. Executive responsibility extends well beyond selecting tools to supporting teams with clear, transparent communication and inclusive engagement. “Leaders must help employees understand why AI is being introduced, how it affects their roles, and where new opportunities emerge. When leaders involve people early and make them part of the decision journey, AI adoption gains trust, acceptance, and effectiveness,” he advises.
This people-first approach reflects Pardoe’s broader conviction that AI value emerges only when humans change how they work. AI systems must embed directly into operational workflows, not exist as detached analytical outputs. Leaders need upskilling to ask appropriate questions, interpret results accurately, and act on insights confidently. “Preparing teams for AI-augmented roles is ultimately a leadership challenge,” Pardoe asserts. “Executives who treat it as such build capability, confidence, and long-term organizational resilience.”
Looking Forward: The Next Frontier
As an author and thought leader, Pardoe identifies critical trends receiving insufficient attention. Intelligent systems will increasingly need to connect, coordinate, and collaborate across organizational boundaries. While enterprises deploy AI in isolated domains, the real opportunity and challenge lie in enabling these systems to work together coherently on a scale.
This evolution requires AI systems to develop a richer understanding of their operating environment and broader organizational context. He predicts that designing future AI platforms that combine general intelligence with deep domain-specific understanding will be a critical success factor. He further notes that the ability to scale intelligence will increasingly become commoditized, and differentiation will no longer come from merely having AI.
A Strategic Imperative
For senior leaders seeking to position AI as a core driver of organizational transformation, Pardoe offers direct counsel. “I invest time in deeply understanding how AI will reshape your industry and competitive landscape. Rather than treating AI as supporting technology, positioning it as a central force defining future business models, operating structures, and sources of value,” he urges.
The most effective leaders proactively shape this transformation, using AI to drive change rather than allowing disruption to be imposed by competitors or new entrants. Pardoe warns that those who fail to adopt this strategic, forward-looking stance risk being forced into reactive decisions and ultimately being left behind as their industries evolve.
Through Informed.AI’s advisory work, VentureFlows VC’s investment focus, and Origin Works’ growth acceleration, Pardoe continues building infrastructure to support organizations at every stage of AI adoption. His unique blend of academic rigor, enterprise delivery experience, and entrepreneurial perspective positions him as a rare guide capable of translating AI’s transformative potential into sustainable business value. For executives navigating this critical inflection point, his message is unambiguous: AI is not merely a technology initiative but the defining strategic capability of the next decade. Organizations that recognize this reality today will shape their industries tomorrow.