Why portfolio management is essential for AI projects

In an era where artificial intelligence (AI), including generative AI, is revolutionising industries, organisations face unprecedented opportunities and challenges. AI’s potential to enhance customer experience, operational efficiency and insight generation is immense. However, AI projects are inherently complex and distinct from traditional projects due to their uncertainty, ethical considerations and stakeholder expectations.

To harness AI’s power effectively, aligning these projects with organisational strategic objectives, while managing their inherent risks and costs, is crucial.

The role of portfolio management becomes critical in this context. By adopting a portfolio approach, organisations can strategically categorise, prioritise and allocate resources to AI initiatives, ensuring alignment with broader business goals and mitigating the risks of ad-hoc experimentation.

Unlocking AI's full potential

AI projects generally involve extensive and often sensitive data, requiring a blend of expertise, including data scientists, ethicists and end users. They are also fraught with ethical, legal and societal challenges. Portfolio management can help organisations overcome these challenges and risks, and achieve the following benefits:

Aligning AI projects with strategic objectives: this ensures that AI projects contribute to and are in harmony with the organisation’s broader vision and goals. This involves aligning AI initiatives with corporate strategies and core values.
Balancing resources and risks: portfolio management addresses the resource needs for AI projects, such as data, talent, technology and infrastructure. It can also help organisations identify and mitigate the risks associated with AI projects, such as technical, operational, ethical and reputational risks, ensuring that they have adequate contingency plans and safeguards in place.
Value optimisation: monitoring AI project performance to ensure delivery of intended benefits and value alignment with stakeholder interests is pivotal, ensuring maximisation of the overall value of AI initiatives.

Mastering AI project success

The successful application of a portfolio approach in AI projects involves a structured process:

Define portfolio scope and criteria. Set boundaries and establish criteria for AI project selection, reflecting on the organisation’s strategic business priorities and risk preferences.
Identify and select AI projects. Focus on recognising potential AI projects or use cases and choose those offering the highest value and benefits with the least associated risks.
Plan and execute AI projects. This critical phase adheres to best practices in project management, encompassing project scope, timelines, budgets and deliverables, while ensuring AI models are ethically and functionally sound.
Monitor and control AI projects. Track project progress, manage deviations and implement necessary adjustments for project success.
Evaluate and conclude AI projects. Finally, assess whether projects have met their objectives, document outcomes and extract lessons for future endeavours.

Central to this approach is the proactive management of change, ensuring smooth transitions and adoption of AI technologies and processes.

Meaningful AI

Gate One champions ‘Meaningful AI’, advocating a transparent, sustainable and ethically responsible approach to AI. This philosophy is grounded in the conviction that AI should not only be functionally effective but also technologically neutral and responsible, keeping humans at the centre of AI-driven change. It’s aimed at building AI literacy and fostering confidence, driving improved outcomes in customer experience and business operations.

Case Study: how a portfolio management approach helped a retail company

A global retail company had a vision to become a leader in AI-driven retail and had launched several AI projects across different domains, such as customer segmentation, product recommendation and inventory optimisation. The company initially faced several challenges with aligning its AI projects with strategic objectives and maintaining transparency and governance.

By leveraging a portfolio management approach, the company achieved a more coherent, transparent and effectively governed AI initiative framework. This led to increased value creation, customer satisfaction and strategic alignment of their AI efforts.

Portfolio management and AI: a winning combination

AI, while disruptive and complex, presents immense potential. However, the unique nature of AI projects requires a strategic management approach. The portfolio approach offers a structured, strategic framework for managing AI projects, aligning them with organisational objectives, balancing resources and risks, optimising value and ensuring ethical compliance.

With our Meaningful AI framework, organisations can navigate the AI landscape confidently, ensuring their initiatives are not only technologically advanced, but also human-centric. This approach empowers organisations to explore AI’s transformative potential, while addressing its inherent challenges and complexities.