Are you running numerous AI pilots, PoCs and experiments – but struggling to decide which ones to scale, prioritise or stop?
What if all you needed to get started was an initiative name and a short description?
From AI Experiments to Strategic Prioritisation
Many organisations are experimenting with AI across different departments. New ideas, pilots and proofs of concept emerge constantly. But deciding which initiatives deserve further investment is becoming increasingly challenging.
BICon Portfolio Steering addresses precisely this challenge.
Over recent months, the platform has evolved into a comprehensive solution for managing AI, digital transformation and innovation portfolios – covering project planning, milestones, risks, resource capacity, financials, business cases, governance and EU AI Act compliance.
But you don't need all that complexity to get started.
AI-Assisted Prioritisation in Minutes
With the MCP-based BICon Initiative Composer, an initiative name and a short description are enough to generate an initial AI-supported evaluation across four dimensions:
- Value & Scale – What is the potential economic impact?
- Technical Feasibility & Explainability – Can the initiative be implemented reliably?
- Governance & Risk – What risks and regulatory constraints need to be considered?
- Strategic Impact – How does the initiative contribute to strategic objectives?
The AI derives these scores from 30 underlying criteria. Users can then review, challenge and fine-tune the assessments before importing the initiatives into their portfolio.
The resulting evaluations immediately feed into an interactive 2×2 Portfolio Map, supporting four strategic decisions:
- Scale – High value and high technical feasibility.
- Pilot – Technically feasible, but business value remains uncertain.
- Assist – Valuable, but requiring human oversight.
- Stop – Limited value and low feasibility.
Within minutes, organisations can begin comparing and prioritising their AI initiatives – without first having to document every project detail, financial assumption or resource requirement.
Start Simple. Scale When Ready.
As initiatives progress, organisations can gradually introduce more sophisticated capabilities – from financial planning and skill capacity management to dependencies, governance, regulatory compliance and executive reporting.
The platform grows with the organisation's needs.
This also reflects a broader shift in enterprise software: Users should no longer have to master the complexity of an application before they can benefit from it.
AI can provide the initial structure, analysis and evaluation, while humans retain responsibility for reviewing the results and making decisions.
Start with a few ideas. Prioritise intelligently. Expand into full portfolio steering when you're ready.
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