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Dynamics Matters Podcast Ep 109: The five pillars of successful AI adoption: pillar 5, Scaling AI
With special guest Andrew Welch, CTO of Cloud Services, HSO.
In this, the fifth episode in our special 5 pillars of successful AI adoption series, we discuss:
✔ What Scaling AI is
✔ Why change management is key to AI success
✔ Why siloed thinking can doom your AI ambition
Scaling AI: A journey beyond implementation
If you want value from your efforts in making AI a fundamental part of your business operation, then this 5th pillar is where the magic will happen. Because it’s the change management part, where you bake the changes you are making, into the organisation. Without it, your AI strategy will fail.
Sustaining AI progress beyond implementation
The essence of scaling AI extends far beyond its initial implementation. Andrew Welch elucidated the core principle—sustaining and broadening the AI strategy forged through preceding pillars: data consolidation, readiness, incremental AI, and differential AI. Welch emphasised the indispensable need to perpetuate efforts, stressing the continual consolidation of data and governance practices to prevent regression into antiquated data management protocols.
People-centric integration and organisational restructuring
Navigating the intricacies of AI integration, the discussion highlighted tailored approaches for end-users and developers. Welch emphasised user behavior changes, advocating for superior experiences akin to Bing's spontaneous itinerary planning during a Melbourne visit. Simultaneously, developers need seamless integration of AI tools into workflows, fostering an AI-centric approach in workload architecture.
Beyond individual perspectives lies the imperative need for organisational metamorphosis. Welch highlighted the pitfalls—such as the use case death spiral and the IT Tower of Babel—hindering progress. The former fixates on specific use cases without fully understanding evolving technological needs, while the latter underscores the detriments of fragmented technology teams impeding collaborative, ecosystem-driven structures.
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Unlocking value through mindset liberation
Breaking free from siloed thinking is a critical element in extracting value from AI. This shift demands holistic realignments—structural, procedural, and cultural—to harness its potential.
Expanding this narrative to broader organisational contexts unveils the multidimensional nature of scaling AI. It demands strategic pivots, seamless technological amalgamation, behavioral adaptations, and structural changes, beyond mere technological prowess.
In navigating the terrain of AI assimilation and scalability, organisations must prioritise agility, adaptability, and collaboration. Encouraging cross-functional collaboration, nurturing innovation, and reassessing traditional hierarchical structures become pivotal in embracing AI's potential at scale.
Scaling AI demands a strategic approach, a resilient mindset, and a transformative strategy to embrace this transformative journey.