Back to Leadership & Organization Blog

Embrace the uncertainty of AI

Embrace the uncertainty of AI

by Sam Bourton, Chris Wigley and Simon Williams

One thing is certain on the path toward grasping and applying artificial intelligence: uncertainty. But what’s also assured is that organizations will unlock value from AI in unexpected places.

A large automobile manufacturer, believing analytics would spark operational insights, discovered just that. Leaders hoped analytics would uncover fresh opportunities to improve the production process, but it actually revealed more sources of inefficiencies (and, therefore, opportunities) to resolve. The data also established that performance variation and efficiencies the algorithms could “see” in the complexity applied a great deal to culture change and people.

In short, AI helps filter the signal from the noise. Working with hundreds of executives, we have identified 10 ways data and analytics applications can help leaders manage with clarity, specificity and creativity.

  1. Think holistically about opportunities across your value chain and up and down your P&L. Leaders discover new revenue streams and increased profitability. They reap greater rewards via intra- or inter-industry collaborations, as retailers, telecommunications companies and banks are finding in elevating customer experiences.
  2. Rethink your definition of ROI – and think like a VC. Focusing only on financial returns can hinder growth. Through AI, transformative value often emerges through experimentation. Leaders who think of their experiments and associated ROI as VC investors consider their portfolios will innovate, learn and succeed faster.
  3. Make diversity a priority beyond gender and race. Diversity that goes beyond gender and race is imperative to successful AI-driven products. It links to the ability to attract top talent and greater profitability. Gender, racial, cultural and age diversity can help prevent algorithmic biases that can derail products and damage brands. Encourage diversity in data sets, data science methods, and academic and disciplinary backgrounds.
  4. Over-communicate the change. Employee adoption of new analytics tools can lag from mistrust in “black boxes” and the fear of losing out to robots. Offer a clear vision and direct communications about why AI is important to company goals, how it can augment employees’ work and the role every employee will play alongside it.
  5. Empower decision-making. Technology is changing at hyper speed, making traditional hierarchical approaches ineffective. Simultaneously, cultural changes and social implications of AI require a controlled framework and strategic vision. Leaders should view themselves as architects, creating a singular vision and plan while empowering decision-making.
  6. Invest in grasping the technology. We don’t believe machines will replace humans; rather, they will augment our intellectual reach, as machines enhanced humans’ physical capacity during the Industrial Revolution. Understand how AI works, what its limitations are , what humans are better at than machines and vice versa.
  7. Think about and own the second- and third-order effects. To ensure fair, transparent and accountable systems to address potential impacts on labor and society, be part of these conversations. Create an ethics committee that considers potential uses and misuses of AI offerings. Encourage critical thinking and debate.
  8. Embed data security into your culture. Security teams should enforce and gamify training to keep employees alert. Ensure decision-makers manage data risk at the policy, technical and cultural level when launching digital products and services.
  9. Keep your tech stack up to date. Challenge your CIO and CTO to make decisions and build a scalable, modular platform for everyday operations as well as experimental machine learning.
  10. Always be learning. Data doesn’t provide the answer, but illuminates the path and provides a valuable feedback mechanism for continued learning and improvement.

AI fosters new business opportunities, risks, responsibilities and insights — all of which require a fresh approach to leadership. Sending AI out into the mass of complexity of an organization without knowing in advance what it will come back with, leaders are embracing the discovery of original, unexpected and breakthrough ideas.