With only 36% of executives reporting a well-defined vision for AI deployment, many organisations find themselves in a precarious position: high on AI adoption but low on strategic direction. In my experience, there is mostly a gap on an overall strategy that is adequate to current pace of disruption and unpredictability in any market. How can you bridge this critical gap?
Aligning AI with Business Objectives
Ensuring AI initiatives support core goals and ensure they are aligned and orchestrated with all technology and transformation initiatives - they will most likely do one of three things:
Make your existing initiatives obsolete
Force a change in strategic positioning or even client/customer proposition
Challenge the current business model
What we recommend: Bring the C-suite and board together to understand the impact and make this decision and stand by it. Test, monitor and judge the data, not the legacy - your business is likely to make money differently in the next 5-10 years.
Where have you seen this?
Kodak - invented the digital camera, but weren't willing to change the business model.
The Pilot Project Trap
Moving beyond small-scale experiments is very complex. Due to the overlap with other projects and technologies, the need for quality data and an appropriate program to address change-resistance or fatigue in the workforce, it's relatively straight forward to build an isolated solution, but complex and painful to scale, integrate and rollout.
What we recommend: Align stakeholders, agree on a pathway to get from POC to full deployment across tech, change and PMO, and empower teams to move fast within clearly defined guiderails and an efficient governance model.
Examples: It's probably all around us - I hear of big telcos and Oil and Gas businesses running anywhere between 100-250 POC's, but would be surprised if they had an operating model and governance process to ensure they progress into the hands of users, and deliver the business value on their business cases.
Cross-Departmental Collaboration Challenges

Breaking down silos for effective AI implementation is imperative, and it must be sponsored by the executive team. We have lost count of the times in which a strategic initiative has multiple versions happening across Tech, Data, Automation, AI and Digital - all trying to solve the same problem, and not aligning nor collaborating to do so.
Our recommendation: Multi-disciplinary teams across most stages of each project, with clearly defined owners and responsibilities (a RACI helps...) and clearly defined handover points, information and governance. Additional tip: Co-location REALLY helps move fast.
Scenario: A company developing Generative AI products sees progress stifled at every step due to lack of alignment with Data teams (for the sourcing and ingestion), Digital teams (also developing products with similar potentially shared components) and Change teams which don't have any of the product rollouts on their roadmap or plans. What could go wrong...
Ethical Considerations and Governance
Navigating the complex landscape of AI ethics is becoming paramount to mitigate the risks created by the application at scale of AI technologies. Governance becomes even more important as companies adopt agile and lean product development cultures, without the continuous monitoring and iteration that guide these methodologies.
Example: Microsoft's Tay experiment which last a few days after disastrous results. But there is also Air Canada's rogue customer service Chatbot who promised discounts that were not on policy. Zillow's debacle with Zillow Offers, which used ML algorithms to place offers on homes, and ended up costing a >$300M write off, and over 2000 layoffs.
Our takeaway: Somethings are just silly to even consider when discussed across different domains and stakeholders, but others only need the right prioritisation and alignment around strategic company goals, that make the business case a no-brainer.
Successful AI implementation requires more than just adoption; it demands a comprehensive strategy aligned with your business goals. Furthermore, most of the barriers are things that can be agreed, managed and addressed when they occur.
Our consultancy specialises in helping you develop and navigate a tailored AI (and probably transformation) roadmap for your enterprise and your culture.
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