08 Sep 2022
What AI means for the Board
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Our experts examine new AI legislation in the EU, how Boards are using AI and the future of the Chief Data Officer role.
What AI means for the Board
The European Union is about to become the first major market to create a legislative framework around artificial intelligence, and Boards of directors need to pay attention.
The European Commission’s Artificial Intelligence Act will impose obligations on developers, including standards of governance, design, transparency, and data security. It is the world’s first legal framework covering AI, and those that fail to comply with it may be subject to hefty fines.
Legislative frameworks like the AI act are necessary and will provide the guidelines to help companies build and implement the technology, ensuring it is used ethically.
As general-purpose AI becomes more powerful and effective in the business environment, it can substantially alter business opportunities, company risk, investment plans, structures, and talent and skills requirements. AI, like every major technology revolution, also has vast potential for disruption. Businesses increasingly see it as a competitive advantage and are going to great lengths to implement AI systems.
It is important to note that AI is not simply a software update. Artificial Intelligence relies on data input to create the underlying code, and the data is continuously analyzed to create or predict new patterns of behaviors. It can be outsourced to a tech vendor to develop and implement and this will fuel the tech industry for years to come. However, this piecemeal approach may not provide the level of data input needed to make AI more effective. It requires collaboration across different parts of the company to ensure emerging risks, such as any bias in the data, are appropriately managed. Even a slight bias in the data can have severe consequences on financial returns and reputation and could potentially breach the EU’s upcoming AI Act.
How Boards should approach their AI journey
Implementing AI effectively (in keeping with the EU’s legislation) first requires a maturity check. This will enable an organization to define the status quo, identify pitfalls and prioritize areas accordingly.
There are approximately four company maturity levels that have been identified when implementing AI. Experimenters, who have successfully completed their first pilot tests; practitioners, who have an AI strategy and have begun actual AI deployment; professionals, where AI is in production and broadly embedded in the organization, and shapers, where the organizational DNA is transformed, and AI is at the core of the competitive strategy.
Secondly, Board members should act as role models for the rest of the company. Bringing clarity to the complexity of AI is very important, as is developing a basic intuitive understanding of AI and its associated skills. The strategic direction, priorities, data-driven actions, support of experimentation, and upgrading the board’s competencies around AI should figure prominently in an organization’s communication and actions. This will mitigate misconceptions, fears, and resistance.
Thirdly, a programmatic approach to the AI strategy is needed, identifying and prioritizing use cases before developing the AI solutions. Lastly, Board members should guide the organizational change process with proven knowledge and best practices and standards.
At the same time, all AI-enabling factors in the company must be upgraded, including data and Machine Learning infrastructure, people and talent, organization, and governance, and ultimately, suppliers and partners.
“Odgers Berndtson has been partner of the appliedAI Initiative, one of Europe’s largest networks for the application of Artificial Intelligence since 2018. Together we have explored the impact of AI on Leadership.”
Says Dr Philipp Hartmann, Director AI Strategy at Applied AI Initiative in Germany.
Every AI initiative requires joint ownership by the business user and technical/process experts – usually IT. This is important as data is integral to the algorithm, and business users are responsible for data input. Therefore, AI requires new skills at levels beyond the Digital or Big Data waves. Processes and applications need to be reconsidered from a data perspective, and data pipelines have to be built—collectively affecting all parts of the organization.
Arguably, the IT function is subject to the largest transformation. It must move much closer to the operational units and acquire new technical, business, and user-interaction skills. AI is a truly company-wide transformation.
Will the role of the Chief Data Officer become the Chief AI and Data Officer (CAIDO)?
Given the complexity of implementing AI within the bounds of an entirely new legal framework, a Chief AI and Data Officer may become a necessity.
A CAIDO would ensure the overall alignment of AI activities and oversee the existing initiatives throughout their lifecycle. Without top-level oversight of the complete AI portfolio and programs, duplication of efforts and waste of resources is likely. Additionally, effective coordination is necessary to leverage all datasets for use within the algorithm.
They will also challenge the status quo from an ‘AI First’ perspective and serve as a sounding board for other board members. A CAIDO should be able to identify and utilize AI opportunities in a variety of different ways and prevent other leaders from pursuing risky AI ventures.
Ultimately, a CAIDO will drive AI initiatives throughout the company. Whether one is needed or not, is likely to depend on several factors such as CIO or CTO skillset, an organization’s AI maturity level, and a Board’s level of knowledge of AI.
The path forward
The combination of new AI legislation and increasing competitor adoption may soon mean that AI representation on the Board is becoming a necessity. Responsibility for implementing and scaling is truly business-wide, and therefore requires, at the very least, Board level competency. Above all, a genuinely collaborative, iterative, and cross-functional company is critical for AI success as its algorithm is only as good as the quality of its data – which comes from the employees.
Dr Andreas Liebl from Applied AI adds:
“We are working hard to help companies advance into the AI age. And with this experience and expertise, we are also interacting with governments and the European Union on the upcoming Artificial Intelligence Act, always with the objective to make Europe the successful Leader in ethical AI.”
To discuss how to approach your AI journey as a Board, or if you need assistance with CAIDO roles, contact the authors' Mike Drew and Markus Trost, get in touch with us here or your local Odgers Berndtson contact.
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