Roadmap to kickstart your AI-ready knowledge strategy

The knowledge era meets the intelligence era

Headlines are inundated with AI agents and agentic AI, but AI isn’t just a headline anymore–it’s changing how we work, learn, and remain competitive. CEOs are calling for departments and employees at every level to embrace AI now, not later, because the stakes are high and the pace relentless. 

But here’s what often gets missed: GenAI, agents, and agentic AI isn’t just about technology. It’s about how organisations retain, develop, retrieve, and share information. We’re moving beyond static documents and information silos. Knowledge has become a living ecosystem that learns, adapts, and anticipates what’s next. And it’s driven by data—much of which is already sitting inside those documents and information silos. 

Organisations that thrive in this new era will rethink not only their systems and processes, but also how they engage and empower people at every level to use AI for opportunities where it makes sense.

Where and how do we start using AI?

It’s a question we hear often now. Along with, “The company is asking how we’re using AI and we don’t know where to start” or “We’re being asked if our data is AI-ready. What does that even mean?” 

Playing with AI to learn how it works and what it can do is a good starting point. But at the enterprise level, start with an AI-ready knowledge strategy.

An AI-ready knowledge strategy blends technology, people, processes, and data—unlocking what many are calling collective intelligence. AI-ready organisations empower their teams to navigate complexity, embrace change, and turn knowledge into a competitive edge.

The cost of doing nothing: What’s at stake?

The cost of standing still is rising exponentially. You risk more than just inefficiency; you risk falling behind, and worse, becoming irrelevant. And yet, moving ahead without an AI-ready knowledge strategy may mean a slow or false start.

According to a global survey by Informatica (1), the three most prominent reasons new AI projects fail are due to

• Data quality and readiness (43%)
• Lack of technical maturity (43%)
• Shortage of skills and data literacy (35%)

Yet another global survey by the Adecco Group (2) found that AI is saving workers anywhere from 1 to 5 hours per day.

These results show the promise and failure of attempts to leverage AI for everything from personal productivity to operational efficiency. Interestingly, the Adecco Group study showed that not all productivity gains were being put to good use with roughly half of respondents saying they either had the same workload or more personal time. No mention was made of an improvement in meeting business goals.

Without an AI-ready knowledge strategy, ad-hoc initiatives may fail, or fail to achieve business goals. In contrast, alignment of technology, people, processes, and data ensures you get to market faster, move into new markets, and deliver on your mission.

Loss of market dominance and ROI

Consider the case of IBM Watson Health. Despite billions invested starting in 2015, the patient treatment AI is reported to have failed to deliver, forcing the sale of the program in 2022. The result—a potential missed opportunity to dominate in the healthcare space, alleged financial losses, and arguably a blemish on the company’s reputation. Even tech giants can stumble without the right foundation. 

Falling behind the competition

Imagine a mid-sized company with siloed, unreliable data and no AI literacy plan. Team members can’t find what they need fast enough to make quick decisions, be more productive, or collaborate and innovate. 

This company will fall behind competitors that have a strategy to leverage AI to make faster, informed decisions, operate efficiently, meet customer needs, and spot emerging trends—enabled by an AI-savvy workforce. 

The knowledge readiness gap

The gap is growing wider between AI-ready organisations and those who have not started their AI journey, or those that have only dabbled with tools.

As the gap widens and the risk of doing nothing increases, companies slow to adopt AI lose out on productivity, innovation, and talent. They risk becoming obsolete.

The strategic value of an AI-ready knowledge ecosystem

An AI-ready knowledge strategy is not an IT project—it’s a collaborative transformation that involves cross-disciplinary teams to plan and requires an entire company to implement. 

Moving from fragmented, siloed information to collective intelligence unlocks business intelligence and leads to innovation, business growth, and agility.

An AI-ready knowledge strategy aligns use cases with business goals, ensures data is machine-readable and has context, and establishes AI and knowledge management governance, while managing change and enabling employees to use AI effectively. 

Think of your company’s information as a jigsaw puzzle. Pieces are scattered across the business. When connected, those pieces becoming holistic knowledge you can use, creating opportunities for moving:

• From reactive to proactive decision-making
• From slow-moving ships to faster, smarter decision-making
• From fragmented knowledge to business intelligence
• From static repositories to adaptive learning systems
• From SOPs and FAQs to enhanced customer and employee experiences
• From legacy systems to future-proof, streamlined operations

The result? Collective intelligence and an innovative culture, as people, processes, data, and technology align to drive business intelligence.

Collective Intelligence is the next evolution of knowledge management: a dynamic, AI-powered ecosystem where information flows freely, insights are generated quickly, and knowledge becomes a competitive edge.

Common pitfalls that sabotage AI initiatives

Even with the best intentions, many AI initiatives fail, because they are just that—initiatives without strategy. Watch out for these pitfalls:

Misconceptions

• Assuming AI is plug-and-play: expecting instant results without laying the groundwork in data, process, and people
• Thinking data is already “good enough”: poor data hygiene leading to incomplete, outdated, or siloed content that undermines AI accuracy and trust
• Making AI an IT problem: treating AI and knowledge management as an IT initiative instead of a shared business priority
• AI is a one-and-done challenge: viewing innovation as a one-off project or siloed department, rather than an ongoing organisation-wide transformation.

Organisational blind spots

• Tech-first, culture-last: jumping into AI without preparing your culture for change
• No clear business case: launching AI projects without clear objectives, metrics, or ROI
• Ignoring change management: underestimating the need to bring people along for the ride
• Lack of cross-functional ownership: failing to involve stakeholders from across the business
• Neglecting governance and security: overlooking data governance, compliance, and ethical considerations

Technical challenges

• Neglecting Governance and Security:  overlooking data governance, compliance, or managing accuracy of growing data volumes
• Lack of semantic expertise: not building in semantic context and expertise to ensure accuracy of AI outputs
• Choosing the wrong tech: selecting AI and knowledge management tools that don’t fit your business needs and can’t scale as you grow

Talent fails

• Retention risks: rolling out AI without a knowledge strategy, leading to disillusionment and burnout
• Low AI literacy: skipping education and engagement, leaving employees confused, resistant, or misusing AI

The AI-ready roadmap: From chaos to clarity

Transformation to an AI-ready enterprise isn’t a short-term or one-off project—it’s a journey of continuous improvement. As AI continues to transform work, an AI-ready knowledge strategy must also continually evolve.

We’ve identified six stages to help enterprises navigate a human-centered AI-ready transformation. Some of these activities will get your content more human-readable too.

These stages start with foundational activities—such as enterprise alignment, AI and knowledge management assessments, governance, AI literacy and data readiness — through the more practical stages of implementation, optimisation, and scaling AI knowledge initiatives. The roadmap concludes with Stage 6, which addresses the building of an innovation culture and the continuous improvement of an AI-ready knowledge strategy.

Your AI-ready knowledge strategy should address all six stages.

Getting started: The first 90 days

Ready to build momentum? If you’re not sure where to start and what your goals for an AI knowledge strategy should be, you’re not alone. 

Most clients we hear from want to prove the value of AI in the knowledge organisation before they take the leap toward a full strategy and then scale. The Altuent AI Accelerator programme helps you do just that—prove value as a precursor to strategy and scale. 

In this program, you’ll focus on proving value with Microsoft Copilot agents, using your SharePoint content as the source for these agents. We find SharePoint is a good starting place because so much valuable enterprise knowledge is languishing in SharePoint.

The programme combines elements of User Adoption and AI literacy with a real use case designed to align with business goals. 

Once you’ve completed the accelerator, you’ll be in a better position to consider how to scale, vertically or horizontally across the enterprise. And you’ll have gained some lessons in how to identify the most valuable use cases for your enterprise. 

Then, you’ll feel confident to develop your enterprise AI knowledge strategy.

The overwhelming reality: Why you can’t do this alone

Developing and implementing an AI-ready knowledge strategy is complex and cross-disciplinary. If it feels overwhelming, that’s a good indicator that you’re considering the right challenges.

The truth is, most organisations need expert guidance to navigate data readiness, technical choices, and the cultural and operational shifts required for successful AI readiness. 

Why partner with experts?

• Proven frameworks and best practices
• Deep knowledge management and content management expertise
• Accelerated outcomes and reduced risk
• Experience in building a culture of innovation that leads to transformation

Been there, done that: The Altuent story of AI-ready transformation

Altuent is proof that transformation to an AI-ready company is possible. We began as a technical writing and content migration company, with localisation and learning expertise, focused on helping organisations document and share knowledge. 

About five years ago, we noticed that AI was beginning to reshape the business landscape, and we saw an opportunity to evolve.

Our specialist teams still help companies structure and migrate content, but with an AI-ready approach.

We didn’t just adopt new technology; we built a culture of innovation. This meant investing in AI literacy across our team, encouraging experimentation, and making change a shared responsibility. We aligned our strategy with our vision—based on the anticipated future needs of our clients—re-imagined our services and developed new expertise in AI-powered knowledge management. 

If your organisation is ready to accelerate, let us guide you. The Altuent AI Accelerator provides you with a strong starting position.