In parts one and two of my series on artificial intelligence (AI), I outlined what constitutes AI and how AI technologies are already being used today in banking, insurance and capital markets. In this final part of the series, I will discuss how companies can craft an AI strategy using a value-driven approach to achieve quick results.

Accenture research on the impact of AI in 12 developed economies reveals that AI could double economic growth rates in 2035 by changing the nature of work and creating a new relationship between man and machine. The impact of AI technologies on business is projected to increase labor productivity by up to 40 percent and enable people to make more efficient use of their time1.

To avoid missing out on this opportunity, policy makers and business leaders should prepare for, and work toward, a future with AI. They should do so not with the idea that AI is simply another productivity enhancer. Rather, they should see AI as the tool that can transform our thinking about how growth is created. Since AI technology opens up entirely new business models, new types of talent and ecosystems will be required.

AI is rapidly coming of age, as business leaders increasingly grasp the immense potential of “smart” machines and other innovations as catalysts for greater efficiency and competitiveness.

To fulfill the promise of AI as a new factor of production that can reignite economic growth, relevant stakeholders should be thoroughly prepared—intellectually, technologically, politically, ethically, socially—to address the challenges that arise as AI becomes more integrated in our lives.

The starting point is understanding the complexity of the issue.

At Accenture, we understand the banking, capital markets and insurance industries. As a leading global professional services company, we are uniquely positioned to provide the broad range of services and solutions in strategy, consulting, digital, technology and operations needed for AI-led growth.

We combine unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—and work at the intersection of business and technology to help you improve your performance and create sustainable value for your stakeholders.

For crafting an AI strategy, we recommend a value-driven approach based on three phases:

Sprint 1: Target Business Opportunities
  1. This phase includes determining the draft AI strategy to validate through project.
  2. It also involves determining likely areas of opportunity against the existing foundational AI capabilities in place, a business problem and use case inventory, and formulating an initial value case hypothesis.
Sprint 2: Identification and valuation
  1. In this phase, we recommend defining the MVP for the projects that can drive impact to the value chain against the “identification” framework. This phase also includes scanning across profitability, growth and sustainability, and rapid prototyping.
  2. We also recommend developing the value case to understand the potential outcomes that can affect the profit, growth and sustainability, as well as understanding workforce strategy, enhancements to foundational capabilities, and no-regret activities.
Sprint 3: Set direction and path
  1. The final phase consists of refining and integrating the strategies and projects, developing the roadmap and direction forward, and developing proof-of-concept (POC) structure.
  2. Finally, we recommend mobilizing no-regret activities, communicating and socializing to drive momentum, and refining approaches based on the results from POC studies.

We can help you implement AI today. And the time to move is now.



  1. Why Artificial Intelligence is the Future of Growth. Accenture, 2016. Access at:


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