Artificial intelligence: What the C-suite needs to know

Investments in artificial intelligence (AI) have grown in recent years and discussions are now shifting from how to create business value with AI to how to do so in a responsible and ethical way. Given the potential of AI for value creation, disruption, and destruction, it is imperative for executives to better understand and manage "the Art of the Possible and the risks of what is possible” with this technology.

The World Economic Forum published the “AI C-Suite Toolkit” to support executives in their Artificial Intelligence implementation decision making. The toolkit provides an approach to AI, covering multiple dimensions businesses need to consider when making investments in AI.

To do so, C-suite executives need to ask the right questions of themselves and their teams. They need to ask not only about what strategic options AI can create but also what can make AI risky and what types of risks they need to consider when deploying AI. They need to identify the most effective organizational design to embed AI across an organization and think about AI governance. This must include what practices organizations can use to ensure AI is deployed ethically, in compliance with new regulations and with a focus on ensuring their customers’ and other stakeholders’ trust

For complex topics such as the implications of AI for business and society, asking the right questions can be as important – or more important – than identifying the potentially many “right” answers. Moreover, getting answers to the questions AI raises requires a multi-faceted approach and holistic understanding of AI that spans technical, organizational, regulatory, societal and even philosophical factors.

“The key skill executives need to develop is the ability to understand the art of the possible with AI while identifying the main risks it creates,” said Kay Firth-Butterfield, Head of AI and Machine Learning at the World Economic Forum. Furthermore, Theos Evgeniou, Professor at INSEAD and Co-Founder of Tremau said, “Organizations need to adopt new data and AI risk management practices, processes and tools in order to both comply with upcoming regulations and to ensure customer trust”,

The promises of AI

Consider the strategic implications of AI, for example. Unlike other technologies, AI has the ability to automatically (or semi-automatically) make decisions, from what products to recommend to which customers; to how to prioritize customers or even patients in medical triage cases. This creates a fundamental shift in the cost base and scalability of businesses as AI can replace people-dependent, variable costs with the fixed costs of AI-enabled software.

“AI is like the Internet: it feels optional until it’s too late. We were delighted to contribute Best Practice AI’s practical digital strategy and transformation experience working with executives globally to this world class effort. C-suite leadership is key to deliver data-enabled business model transformation - and senior management learning critical to ensure that this is done ethically and sustainably,” said Simon Greenman, Partner at Best Practice AI and Member of the World Economic Forum’s Global AI Council

Business metrics traditionally affected by technology can also be improved with AI, from KPIs related to customer satisfaction or engagement to process efficiency metrics or employee productivity.

AI maturity and organizational readiness

While the opportunities increase as the AI capabilities of organizations mature, the journey of an organization to AI maturity is not an easy one. Executives need to be able to assess their organization’s AI maturity and then understand the roadblocks to progress. They must consider the organizational and cultural changes that need to be made and those that will occur following the introduction of AI.

“With our strong expertise in manufacturing consultancy and +100 SIRI maturity assessments, we see that the foundational knowledge of AI in operationalizing the strategy is visible as a common need. Global research on the subject confirm that using AI has benefits like providing cost reduction, inventory minimization, quality increase, profit optimization, etc., and potential risks like strengthening inequalities. Creating a platform for understanding the benefits and mitigating the risks is required, especially at the executive level. With the modularity and extensive understanding of AI, this toolkit will be a reference guide for all leaders,” said Efe Erdem, MEXT Group Director & Head of C4IR Turkey. “

Defining the appropriate organizational design with which to embed AI and data-driven decision-making across an organization is complex. Multiple challenges must be overcome to align AI with all parts of the organization, from engineering to customer-facing units, and to upskill the workforce effectively. Success – even at the level of specific AI project implementations – is not a given: executives need to understand new project execution risk factors (beyond usual ones such as change management challenges) that can lead to costly project failures. These may include very challenging data issues or difficulties from continuous risk management of the AI models deployed.

“As an advisor to C-suite executives of organizations aspiring to become AI and Data-driven, we have observed firsthand how fundamental it is for leaders to understand how to make informed decisions such that their organizations can truly reap the benefits of AI in the coming years,” said Nihar Dalmia, Canada Government and Public Services Leader, Omnia AI, Deloitte.

The potential AI risks organizations face

With power comes responsibility; this is true for AI. The ability of AI-enabled systems to make automatic decisions leads to a number of new risks, from privacy infringement to potential discrimination, for example, when similar customers are treated differently by AI; to new safety and security risks.

Executives need to understand not just how their organizations can adopt AI, but how to do so responsibly. “Successful” adoption of AI may prove costly in the long term if these new risks materialize. Success with AI is both a matter of value creation and of risk management for the business. Executives need to answer questions such as: what are the new risks AI creates for my business? How can we manage these risks? What is the role of AI governance and how can we best think about it?