Treat AI initiatives as two separate strategic pillars. Create one roadmap focused on internal efficiency gains and cost reduction (productivity). Maintain a separate roadmap for developing new, revenue-generating customer experiences (growth). This prevents conflating internal tools with external products.
An effective AI strategy pairs a central task force for enablement—handling approvals, compliance, and awareness—with empowerment of frontline staff. The best, most elegant applications of AI will be identified by those doing the day-to-day work.
The true ROI of AI lies in reallocating the time and resources saved from automation towards accelerating growth and innovation. Instead of simply cutting staff, companies should use the efficiency gains to pursue new initiatives that increase demand for their products or services.
Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").
Using AI for incremental efficiency gains (10% thinking) is becoming table stakes. True competitive advantage lies in 10X thinking: using AI to fundamentally reimagine your business model, services, and market approach. Companies that only optimize will be outmaneuvered by those that transform.
Most companies use AI for optimization—making existing processes faster and cheaper. The greater opportunity is innovation: using AI to create entirely new forms of value. This "10x thinking" is critical for growth, especially as pure efficiency gains will ultimately lead to a reduced need for human workers.
C-suites are more motivated to adopt AI for revenue-generating "front office" activities (like investment analysis) than for cost-saving "back office" automation. The direct, tangible impact on making more money overcomes the organizational inertia that often stalls efficiency-focused technology deployments.
To find valuable AI use cases, start with projects that save time (efficiency gains). Next, focus on improving the quality of existing outputs. Finally, pursue entirely new capabilities that were previously impossible, creating a roadmap from immediate to transformative value.
While AI-driven efficiency is an obvious first step, it often results in workforce reduction if company growth is flat. True differentiation and sustainable advantage come from using AI for innovation—creating new products, markets, and business models to fuel growth.
Adopt a 'more intelligent, more human' framework. For every process made more intelligent through AI automation, strategically reinvest the freed-up human capacity into higher-touch, more personalized customer activities. This creates a balanced system that enhances both efficiency and relationships.
To balance security with agility, enterprises should run two AI tracks. Let the CIO's office develop secure, custom models for sensitive data while simultaneously empowering business units like marketing to use approved, low-risk SaaS AI tools to maintain momentum and drive immediate value.