Category: Organizational development

  • The AI Implementation Gap: Why Only 14% of Companies Are Successfully Scaling AI

    The AI Implementation Gap: Why Only 14% of Companies Are Successfully Scaling AI

    In a world where AI dominates headlines and board discussions, it’s easy to assume that most organisations are successfully implementing artificial intelligence at scale. However, a recent global survey highlighted in the Financial Times paints a starkly different picture: while all UK and US companies surveyed are using or planning to use AI, only 14% have managed to scale beyond the pilot stage.

    The AI Adoption Paradox

    This statistic reveals a significant paradox in AI adoption. There’s nearly universal recognition of AI’s importance—McKinsey estimates increased market fit of up to 50%, product performance improvements of 15-60%, and up to 40% reduction in time to market for companies effectively leveraging AI. Yet, the vast majority of organisations remain stuck in experimental phases, unable to realise these transformative benefits at scale.

    As Sean Ammirati, professor of entrepreneurship at Carnegie Mellon University, aptly puts it, we’ve reached a “general technology inflection point” similar to the early internet era. Companies that choose to avoid embracing AI fully may face the same fate as those who once dismissed the internet as a passing trend.

    Key Barriers to Successful AI Implementation

    The Financial Times article identifies several critical impediments that explain this implementation gap:

    1. Talent shortage: Particularly amongst UK respondents, the lack of AI-skilled talent emerges as a primary obstacle. Organisations that quickly invest in educating and upskilling their current workforce will gain a significant competitive advantage.
    2. Poor data management: AI systems function as statistical models that feed on data. Without clean, well-structured data, even the most sophisticated AI tools will struggle to deliver value.
    3. Misaligned priorities: Many organisations fail to identify the most strategic applications for AI implementation, leading to scattered efforts that fail to demonstrate meaningful business impact.

    The “Human + AI” Future of Work

    Despite concerns about job displacement, the article emphasises that AI is far from replacing human workers. The optimal approach is what experts describe as “human in the loop AI”—viewing AI as a collaborative partner rather than a replacement.

    “The right mental model is to think of generative AI as a co-founder… like a brainstorming buddy, more like someone who automates first drafts than does all the work for you,” explains Ammirati.

    Implications for Your Organization

    At CMinsights, our AI Organisation Readiness Assessment Framework (AIORA) directly addresses these challenges. We’ve structured our framework around three essential building blocks that align perfectly with overcoming the identified barriers:

    1. People: Focusing on workforce transformation, change management, and AI literacy development to address the talent gap
    2. Leadership & Strategy: Ensuring strategic alignment, ethical governance, and leadership readiness to guide appropriate AI prioritisation
    3. Organisation: Developing the necessary structural flexibility, cross-functional collaboration, and adaptive systems to support AI integration

    The Path Forward

    For organisations looking to join the elite 14% successfully scaling AI, the message is clear: AI implementation is not merely a technical challenge but an organisational transformation requiring a systematic approach to people, leadership, and organisational structures.

    The time for piecemeal experimentation has passed. As the FT article concludes, AI adoption “is no longer optional.” Organisations that fail to develop a comprehensive approach to AI readiness risk falling behind more agile competitors who effectively harness AI’s transformative potential.

    Ready to assess your organisation’s AI readiness and develop a strategic roadmap for implementation? Our consulting services are designed to help you navigate this complex transition and join the leading organisations successfully scaling AI across their operations. Contact us today to join the leading organisations successfully scaling AI across their operations.

    *This blog post was inspired by insights from a Financial Times Tech for Growth Forum report on AI and the R&D Revolution.

  • AI Organizational Readiness: Preparing Your Workforce for the Future

    AI Organizational Readiness: Preparing Your Workforce for the Future

    In today’s rapidly evolving business landscape, artificial intelligence is fundamentally reshaping how organisations operate and how work gets done.

    The recent HBR article “How Gen AI Could Change the Value of Expertise” by Joseph Fuller, Matt Sigelman, and Michael Fenlon highlights a critical insight: AI will significantly impact approximately 50 million jobs in the coming years, with some career paths becoming more accessible while others face higher barriers to entry.

    This presents both challenges and opportunities for organisations. The question isn’t whether AI will disrupt your workforce—it’s how prepared you are to navigate this change proactively.

    Understanding AI’s Impact on Your Organization

    Our research through CMinsights has revealed that organizational readiness for AI isn’t merely about technology adoption. It requires a comprehensive approach that addresses three foundational building blocks:

    First, we must consider People – the individual human capabilities, adaptability, and readiness for AI integration.

    Second comes Leadership & Strategy – the vision, direction, and governance mechanisms needed to guide transformation.

    Finally, we must address the Organisation itself – the structures, systems, processes, and cultural elements that enable effective AI integration.

    These three areas form the foundation of what we call the AI-ORA Framework (AI Organizational Readiness Assessment), which helps organizations systematically evaluate their preparedness across 18 dimensions.

    The Shifting Value of Expertise

    As Fuller, Sigelman, and Fenlon note in their research, AI is reshaping learning curves in fascinating ways. For roles with steep learning curves like software engineers, credit analysts, and project managers, AI might amplify the productivity of experienced workers while reducing entry-level opportunities. Conversely, for roles where technical skills can be more easily taught, AI could lower barriers to entry and open opportunities.

    This has profound implications for organizational structure. Traditional pyramid-shaped organizations with many entry-level workers supporting smaller numbers of experienced staff may transform into more diamond-shaped structures. Organizations need to anticipate these changes and develop new talent strategies accordingly.

    Five Steps to Build AI Organizational Readiness

    Based on our PACE framework (Prepare, Assess, Cultivate, Evolve), here are five essential steps organizations should take:

    First, conduct a comprehensive assessment. Evaluate your current state across all three building blocks—people, leadership, and organization—to identify strengths and gaps.

    Second, prioritise strategically. Use our CORE framework (Current capability, Organizational impact, Risk & resistance, Ease of enablement) to identify high-impact areas that align with your strategic objectives.

    Third, develop new learning pathways. As traditional career progression paths shift, create new opportunities for skills development that prepare workers for AI-augmented roles.

    Fourth, build change management capabilities. The psychological and cultural dimensions of AI adoption are often overlooked but critical to success.

    Finally, foster cross-functional collaboration. Break down silos between technical and domain experts to ensure AI initiatives address real business needs.

    Building Your AI Talent Strategy

    The transformation of learning curves highlighted in the HBR article demands a reimagining of talent strategies. Organizations should rethink recruitment as entry-level opportunities in some fields decline, creating new approaches to building talent pipelines.

    They should also prioritize retention since competition for experienced workers in fields where AI enhances expertise will increase. Developing internal capability through robust learning and development programs will help existing employees adapt to changing skill requirements.

    Cultivating company-specific knowledge becomes increasingly valuable as AI automates more generalized skills.

    Moving Forward with Confidence

    The AI revolution presents both challenges and opportunities for organizations. Those that take a systematic approach to assess and build organizational readiness will be best positioned to thrive.

    At CMinsights, our consulting services help organizations navigate this transformation through comprehensive assessments, strategic advisory services, and specialized training programs. Whether you’re just beginning your AI journey or looking to accelerate your transformation, a structured approach to organizational readiness is essential.

    The future of work is being shaped right now. The question is: will your organization be ready?