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Why enabling AI’s full value requires top-down thinking

Photographic portrait of Dan Diasio

4 minute read 24 May 2023

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To realize AI’s full potential to change business, companies should develop AI capability in a way that is integrated and top down.

In brief

In today’s world, companies need to be digital at their core by embedding data and AI into their comprehensive business strategy.
Organizations should incorporate trust into systems from the design stage and build an architecture to implement intelligent automation workflows at scale.
Getting data and insights-driven transformation right will create long term value for customers, people, society and the bottom line.

Excitement about AI is at an all-time high. ChatGPT, a conversational AI tool, can write poetry, prepare speeches and perform an extraordinary array of research tasks at lightning speed, from coding to copywriting. From a corporate perspective, executives have bought into AI, with projections of increased spending as firms across sectors seek to harness capabilities at which AI excels, such as automation, prediction and modeling. Forrester’s Global AI Software Forecast, 2022 predicts off-the-shelf and custom AI software spend will double from $33 billion in 2021 to $64 billion in 2025 and will grow 50% faster than the overall software market, with an annual growth rate of 18%.

Yet many companies are still waiting for the true breakthroughs for enterprises and have yet to see the expected value. In 2022, only 22% of organizations in one IDC survey reported that AI is implemented on a large scale as part of the enterprise. AI’s promise to change business and transform how markets evolve has yet to happen at scale.

A key challenge is that AI capability is often developed through bottom-up initiatives, with Centers of Excellence (CoEs) building portfolios of projects focused on proving AI can surpass existing processes. These are often led by technical teams but disconnected from the wider business. The problem is structural, as the people spearheading AI projects tend to only control part of the value stream; the cross-functional, cross-silo way of extracting and creating value in the business. To truly capture value, AI needs to initiate a wider business transformation, requiring a new approach.

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Boosting AI’s value with top-down thinking

To realize AI’s full potential, companies should develop AI capability in an integrated way and from the top down. To reorient AI strategy in this way, bolder questions are needed. Rather than asking whether AI can improve performance in a specific process, you should ask if AI is helping your business as a whole differentiate itself from your competitors, while helping you become more resilient to the disruptors coming for your business. Is AI allowing you to go after a new market or reimagine your business model?

AI should not be deployed uncritically, of course. But the key to success is to evaluate it like a private equity investor weighs up a business – not asking, “What is a performative North Star?”, but rather "What is the investment thesis” with AI? The private equity sector does this exceptionally well, ensuring a clear line of sight to achieving a differentiated return.

This approach is critical in AI now more than ever. At companies that already excel in AI, programs are driven by Chief Executive Officers (CEOs), who are positioned at the top to drive the change in culture required for success. Tech-savvy CEOs align with their tech leaders, Chief Information Officers (CIOs), on the importance of technology in driving business strategy and performance. They make technologies like AI a leading focus to execute business goals. They don’t develop a technology strategy – they embed technology into the business strategy.

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AI should drive major shifts in revenue and business model transformation, help a firm enter a new market, or fend off a major threat. The goal is not to use AI to do customer analytics for interesting insights, for instance, but to shift the business model from business-to-consumer to direct-to-consumer powered by customer analytics. AI’s value is not in helping finance departments produce machine-learning-powered forecasts on a quarterly basis, but instead to provide daily insights to business leaders on the next best steps to improve profitability. These probing questions will better elicit AI’s power to deliver truly transformational business value.

Key AI questions for transformation leaders

To pursue a more effective strategy, decision-makers should start from a new strategy or a challenge – a new business model, a high cost, a business risk, or a sector they could start to compete in – and ask how AI could help. This allows them to take an offensive position in facing off competitor threats and disruption or to become a disrupter themselves into new markets. This in turn enables AI to be fully supported and resourced by the executive. Useful thought-starters and questions could include:

Do you have an “AI portfolio” or a “Transformation portfolio?”
Is AI being developed in a way that will power your people and business to be unique and best-in-class in a way that it is not currently?
Do you have a professional development plan in place for your people that includes new AI-related training programs, career paths, retention methods – as well as ways to reward new AI skillsets?
Are you leveraging ecosystem relationships for exploring new business models and growth opportunities?
Is AI preparing you for the biggest threats on your horizon?

Summary

Companies that build AI into their overarching business strategy, rather than using it to drive piecemeal processes, have a better chance at realizing the value of AI and transforming from the top down.

About this article

Photographic portrait of Dan Diasio

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