The desire to have faith in new technology by itself as the ‘silver bullet’ to data challenges runs strong in leaders of data teams. In my experience this is not sufficient and often leads to sub-optimal outcomes. It relegates people (particularly) and process to the sidelines, it also underestimates the importance of these to overall success – notwithstanding their challenges. Here is my view on the additional areas that can greatly increase the likelihood of positive results in operations and can significantly boost your chances of a successful data transformation; presented as a contrast between Digital and AI-first organisations and Legacy Enterprises.
1. Architecture
Architecture is destiny. Digital and AI-first organisations benefit from building contemporary scalable frameworks and platforms designed for connected and seamless data flows, with consumption and re-use in multiple use cases, from the start. Legacy enterprises, by contrast, are trapped in a labyrinth of outdated data systems, where each ‘upgrade’ piles complexity onto an already fragmented foundation. It’s akin to endlessly renovating a house where no room matches the next – eventually, nothing works in harmony. Legacy architectures, born in a siloed, physical world, struggle to adapt to the dynamic, interconnected data landscape of a modern organisation. Meanwhile, digital and AI natives thrive, leveraging flexible architectures that integrate easily, enabling them to pivot, scale, and innovate.
Opportunity: “Think Modern, Build Modular” – Break-free from monolithic thinking. Move to designing for flexibility and re-use. Map your current data ecosystem, then create modular interfaces that enable gradual modernisation without disrupting operations, dialling up as you mature. Build to evolve.
2. Mindsets
At the heart of transformation lies mindset. Legacy organisations default to a fixed mindset, clinging to familiar processes and metrics, finding comfort in what worked before. This mindset also encourages a bias towards underestimating the effort required to transform and overestimating the ability of existing capability to deliver it. Digital and AI-first enterprises see today and tomorrow differently. They embrace a growth mindset, where change is the norm and innovation a daily practice. Transformation here isn’t a project; it’s a mindset shift that permeates every level of the organisation. For legacy players, the change challenge is clear: can you move beyond the comfort of the status quo to embrace the opportunity of what could be in the ‘art of the possible’.
Opportunity: “Cultivate Data Thinking” – Foster a culture where data is seen as a strategic asset, not just a byproduct of operations available for reactive analysis. Encourage openness and exploration, where data drives decisions. Celebrate small wins, encourage experimentation, and make learning from a considered action that fails acceptable. Remember that mindset transformation starts with leaders modelling this behaviour.
3. [MIS]Alignment & [DYS]function
True transformation requires a symphony, not a cacophony. In legacy enterprises, misalignment across leadership, technology, and the business creates dysfunction that stalls data transformation progress. Silos, competing priorities, and fractured communication turn strategy into a slow grind. Digital and AI-first organisations sidestep this chaos by fostering tight alignment from the outset. Leadership, the business and data teams are synchronised, sharing a common vision and language to build to. This alignment enables coordinated action, ensuring data strategies don’t just exist on paper – they come to life.
Opportunity: “Build Bridges, Break Silos” – Create a unified data language connected to business outcomes and the domains of business owners. Develop clear data ownership models that encourage collaboration rather than territorial behaviour. Establish cross-functional teams who control end-to-end delivery to strengthen the connection between data capabilities and business outcomes.
4. Agility vs Bureaucracy
Speed + flexibility is the new currency of success, with time to value a key metric. Digital and AI-first organisations are built and structured for agility, operating in short cycles of value delivery to test, learn and iterate with customers. They are comfortable in driving towards a destination, whilst being open to the steps taken on the journey, rapidly seizing opportunities that present themselves at different points. Legacy enterprises, however, often find themselves mired in bureaucracy. Layers of approvals, rigid structures, and risk-averse cultures slow decision-making to a crawl. By the time an initiative clears the labyrinth of internal processes and signoffs, the market has moved on – a transformation in this environment often never completes. Digital and AI-first enterprises embrace agility as a key competitive advantage, empowering their teams to act decisively, iterate quickly, and capitalise.
Opportunity: “Start Small, Scale Smart” – Critically identify areas where ‘the system’ creates the most friction in data initiatives. Create more streamlined processes for lower risk, higher value projects. Empower teams with clear decision-making frameworks rather than rigid approval hierarchies. Start with a small number of prioritised projects, grow as the new way is embedded.
5. Talent & Skills Gaps
Transformation isn’t just about the technology – more and more it’s about the people. Digital and AI-first organisations attract and recruit talent that is on-balance already individually operating with the contemporary mindsets and practices required. They do not have to invest the same level of time and resources in change management. Legacy enterprises face a starkly different reality: a growing skills gap and a struggle to attract and retain the talent needed for modern data and AI capabilities. Too many roles remain anchored in outdated paradigms, stifling the innovation essential for progress. Performance remains below leadership expectations and benefits are never completely realised from the investments made.
Opportunity: “Grow Your Own, While You Transform” – Prioritise adaptable mindsets and learning capability in all people when hired, including in data. Create an environment of continuous learning and actively develop internal talent in those with the right aptitude. Understand that building richer and deeper human capital is a significant asset.
These five elements create a powerful multiplier effect when addressed holistically. Modern architecture provides the foundation for agility, while the right mindset enables its adoption. Strong alignment ensures this agility translates into meaningful outcomes, not chaos. Together, these elements create an environment that attracts and retains top talent, who in turn push architectural innovation and strengthen the organisation’s digital and AI-first mindset. It’s a virtuous cycle where progress in one area accelerates advancement in others. For legacy enterprises, understanding these interconnections is crucial – trying to transform one element while ignoring others often leads to stalled progress.
Digital and AI-first enterprises often seem to be leading simply because of the ‘bright, shiny toy’ of new technology that they leverage. In this article I have outlined additional elements that are often overshadowed in the narrative, but in my experience are critical elements that enable Digital and AI-first enterprises to be so much more competitive and successful. For legacy organisations, addressing these elements in a data transformation isn’t just beneficial—it’s essential to remaining competitive in an increasingly data-driven and AI world.
Simon is a senior leader in AI, Data and Digital, specialising in Strategy, Transformation and Product. He builds enterprise capabilities that drive measurable business value and deliver exceptional customer experiences.
https://www.linkedin.com/in/simonbelousoff/


Part 2 of 2: The Critical Role of CDAOs: Are They Here to Stay?
