Four key lessons on AI strategy for leaders

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By Tor W Andreassen

16 April 2024 14:41

Four key lessons on AI strategy for leaders

As artificial intelligence (AI) changes industries and businesses globally, various AI approaches in the media industry offer insights into strategies for making businesses more resilient to future challenges.

Being at the forefront of AI's impact, the media industry highlights the technology's inherent challenges. Two prominent examples of these challenges are fake news and AI-generated content. As the media industry experiments through these challenges and opportunities, other leaders can learn from the approaches of the Financial Times and AXIO.

The Financial Times, which has always focused on journalistic integrity, has taken a cautious approach. Acknowledging the potential risks of AI-generated content, FT's editors have underscored the need for journalistic oversight and transparency. The editors refer to a plan for responsible integration of AI, focusing on accuracy, fairness, and the importance of journalism conducted by humans. FT's commitment to responsible, human-centric technology integration reflects the arguments of Bostrom and Yudkowsky (2014) regarding the critical importance of ethical guidelines in AI development. The message to employees and readers is editorial responsibility, integrity, quality, and trust.

The leadership of the media company Axios, as mentioned in The New York Times, has, one year after FT, adopted a more proactive stance. Motivated by CEO Jim VandeHei's belief that AI will fundamentally alter competitive dynamics, Axios has transformed its business model and editorial strategy. Axios' four-point strategy - trust, expertise, practical use, and human presence - demonstrates how organizations use AI to enhance their core functions while strengthening relationships with their employees and customers. Axios' proactive strategy mirrors Christensen, Raynor, and McDonald's (2015) theory of disruptive innovations, where adaptation to new technologies is seen as the key to competitiveness. Axios's leadership echoes FT's message but adopts a more progressive stance on utilizing AI in value creation and capture.

I can see four things leaders in other industries can learn from the Financial Times and AXIO.

  1. Balance innovation with principles: Organizations ought to follow the Financial Times' example by actively harnessing AI's power that aligns with their core values and ethical standards. For example, by introducing AI with clear ethical guidelines that align with the organization's values.
  2. Prioritize human expertise: Axios' emphasis on investing in subject matter experts and promoting personal engagement underlines the enduring value of human knowledge and connections. As AI becomes more prevalent, the ability to provide specialized, high-quality content and meaningful dialogues with customers will be a key competitive advantage.
  3. Adapt business models for the AI era: Axios' shift towards subscription-based membership programs and tailored news delivery highlights the need for organizations to reconsider their revenue streams and business models considering AI.
  4. Adopt a culture of innovation: Both Financial Times and Axios have shown a willingness to experiment and adapt, whether through FT's responsible integration of AI or Axios' bold strategic changes. Cultivating an innovative mindset can help organizations stay ahead and leverage emerging technologies.

As AI continues to reshape industries, the lessons from the media industry's various approaches can guide leaders in other fields. By balancing innovation with principles, valuing human expertise, developing business models, and promoting a culture of adaptability, organizations can navigate the AI-driven future with confidence and success. Leaders must continually assess and adjust their strategies to exploit the potential of AI ethically and effectively.

Tor W Andreassen is a Professor of Innovation at NHH Norwegian School of Economics and currently a Visiting Professor at The Institute for Manufacturing (IfM) at Cambridge University.