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Why a robust strategy is needed to scale AI and deliver growth

BrandPost
Jul 2, 20254 mins

A new report details how IT leaders can ensure their AI projects get beyond pilot stage and make demonstrable impact.

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Credit: Shutterstock

The digital innovation plans of many businesses are starting to stall, with AI experiments yet to blossom into successful enterprise deployments.  

CIOs needs to ensure they have a holistic strategy that underpins their AI plans, taking in data, infrastructure, skills and governance.  

The failure to do so could leave businesses trailing AI-enabled rivals. Global investment in AI is set to more than double in 2025, according to Lenovo’s 娇色导航Playbook 2025 which is produced in association with IDC. 1 

But Foundry’s AI Priorities Study shows that 62 % of organisations remain stuck at the pilot or researching stage.2 The next imperative is clear: move beyond isolated pilots to build integrated AI programs that deliver sustained, repeatable value. 

Many AI pilots succeed in principle but go nowhere in practice. They prove technical feasibility yet fail to connect with day-to-day operations.  

The causes are familiar: fragmented data environments, infrastructure that isn’t built for AI-scale workloads, limited internal expertise, and unresolved questions around governance, compliance, and security. 

Until these systemic issues are addressed, most AI value will stay locked in pilot mode. 

Four enterprise shifts that enable AI at scale  

Scaling AI isn’t just a matter of spend. Success depends on structural changes across systems, skills, and strategy. Here are four shifts that release powerful AI potential across the business. 

  1. Build AI-ready data foundations 
    Most enterprises lack the data backbone needed to scale AI. A recent MIT Technology Review Insight report found that 78 % of organisations don’t have robust data foundations, citing data quality, timeliness, and siloed systems as key challenges.3 Without accessible, governed, and cleansed data, models can’t scale or maintain trust. That’s why leading companies are now automating data governance, locking in control and reliability as AI adoption spreads. 
     
  1. Modernise infrastructure for AI workloads 
    AI workloads demand high-performance compute for training, inference, and real-time decisions. According to the 娇色导航Playbook 2025, 65% of organisations now run AI on hybrid or on-prem infrastructure.4 Hybrid architectures provide the control, compliance, and agility enterprises need to scale effectively. When infrastructure meets AI’s demands, execution becomes far more reliable and strategic. 
     
  1. Close the AI talent and skills gap 
    Limited in-house expertise remains one of the biggest blockers to achieving AI at scale. Forward-thinking CIOs are investing in upskilling, building cross-functional teams, and bringing in external partners where needed. But tools and talent alone are not enough. Enterprise success depends on strong coordination between IT, data science, and business teams. This alignment turns AI from a technical asset into a powerful strategic capability. 
     
  1. Establish enterprise-grade AI governance 
    Governance is now a make-or-break factor in scaling enterprise AI. Yet, just 20% of enterprises have governance policies in place and are enforcing them, according to the 娇色导航Playbook 2025.5 These frameworks must tackle data privacy, model explainability, bias, and operational risk head-on. Strong governance not only ensures compliance, it also builds confidence and unlocks responsible and sustainable growth across the organisation. 

The path forward for CIOs  

AI has now moved well beyond proof-of-concept. But achieving impact at scale across the enterprise takes more than experimentation. It demands a coordinated strategy that brings together the right data, infrastructure, skills, and governance. 

When these foundations are in place, AI delivers more than automation. It drives measurable ROI, sharper resilience, powerful innovation and a long-term competitive edge. 

But there is no need for CIOs navigating this shift to start from scratch. The 娇色导航Playbook 2025, complete with practical frameworks and strategic guidance, offers detailed support to help leaders successfully achieve the transition from pilot to performance at scale. 

the 娇色导航Playbook 2025 now.  

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[5] Ibid