Alignment does not require every team to work in the same way. ZHICE sees energy businesses needing both operational stability and learning about immature models. One budget rhythm and one scorecard can subordinate exploration to short-term certainty, or allow innovation language to dilute operating discipline.
Of surveyed AI users report clear and consistent leadership alignment on AI1
2026 · cross-industry survey in 10 marketsZHICE sees misalignment translating into resource disputes, conflicting permissions and duplicated investment. As technology use expands, authority to change workflows, accept risk and own outcomes needs to become clearer. Effective governance reduces waiting and rework, enabling action within explicit boundaries rather than simply adding approvals.
READING THE OPERATING MODEL
Cost, quality, reliability and cash flow generally provide meaningful tests for existing operations. Persistent deviations require explanation, while standardisation can create efficiency under relatively stable conditions.
Early ventures may not know whether customers will pay, capabilities can be reused or risks can be allocated. A focus on current revenue alone can encourage expansion of untested assumptions.
Completely detached innovation teams may lack access to assets, customers and field expertise. Their interfaces with the core business determine whether learning is absorbed and when work should enter stable operation.
Established activities need repeatable outcomes; exploration needs sound evidence, resolved assumptions and controlled commitments. Both require clear ownership.
Where expertise, data and customer access are scarce, the strongest department should not automatically determine their use. Discuss opportunity value and effects on current operations.
Successful validation still requires steady accountability, operating capability and customer commitments. More pilots do not constitute a sustainable new business.
Not every improvement needs a separate innovation mechanism. Clear objectives with established implementation paths may be served better by the normal operating system.
Are we assessing an experiment as if it were a mature business, or using experimentation to avoid operating accountability?
Established businesses need reliability, efficiency and consistent rules; new ventures need experimentation and rapid learning. One budget and performance system can suppress exploration, while complete separation can cut ventures off from resources, customers and expertise.
Distinguish exploration from operations using demand certainty, technology maturity and delivery risk, rather than departmental names or project labels.
Give exploratory work learning goals, bounded budgets and stage reviews. Retain operating-performance requirements for established businesses and arrange shared experts and customer interfaces.
Move validated offerings into operations with a receiving team, capability plan, funding and exit conditions. Prevent innovation from remaining permanently in pilot form.
Exploration and operating-task portfolio
Differentiated funding and performance principles
Pilot-to-operations stage mechanism
The approach draws on organisational ambidexterity research; the design depends on scale, task and risk conditions.
2026 survey of around 20,000 AI users across 10 markets; self-reported leadership alignment, not an energy-sector adoption rate.
2026 · cross-industry survey in 10 marketsAround 60% of energy firms in the IEA 2025 survey reported skills- and labour-related hiring difficulties; the company subsample exceeded 400 firms.
2025 · IEA energy-company surveyEuropean Commission context for the 2023 Grid Action Plan: 40% of EU distribution grids were over 40 years old. This does not describe China’s asset-age profile.
European Commission’s 2023 action-plan context · EU