Artificial Intelligence is here to stay. Board and Management considerations.

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Artificial intelligence (AI) has captured unparalleled media attention over the past two years. The capital flows and stakeholder interests drawn to AI solutions has never been greater. This adoption is expected to continue indefinitely and to accelerate. This commentary highlights the considerations for boards of directors, executive management, and technology leaders in considering how to most effectively use AI to the benefit of all stakeholders. Our comments are based on our discussions at Trask with its clients across the EU, UK, and North American markets.

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John T. Weisel, North American Leader at Trask

[.infobox][.infobox-heading]Key takeaways:[.infobox-heading]
–⁠ Artificial intelligence is not new. It‘s centuries old in concept with adoption accelerating geometrically over the past 30 years.
–⁠ The most significant issue to address is - How through the adoption of artificial intelligence can business value be created at an acceptable level of investment and risk?
–⁠ Human work will not be replaced in totality for any business function, however, the workforce model, roles and scope of responsibilities will change.
–⁠ Central to successful AI adoption is the effectiveness of governance and oversight. Use case selection, data centricity, and flawless execution. The social and technical impediments of before no longer exist.
–⁠ The overall cost of technology will increase, but the investment returns and business value derived will be super normal if adoption effectively executed.[.infobox]

How did AI arrive so quickly?

AI‘s evolution began over 75 years ago, with simple rules-based engines and leading to machine learning that is now routinely utilized across industries. Alan Turing, is a well-known British mathematician and cryptanalyst, who helped to crack much of the Axis Powers communication code during WWII, laid much of the foundation for modern AI. He was characterized in the successful film The Imitation Game in 2014. A must watch for any intelligence aficionado.

At that time in the 1950s, barriers from limited data handling capability, storage availability, and high computing costs, initially hindered AI‘s practical implementation. However, technological advancements over the next two decades led to more accessible and powerful computers spurring AI growth. AI today has entered a new phase. AI can today and will over time mimic human decision-making and will influence every industry, driving shareholder value through improved operating efficiency, enhanced client and employee experiences, and increased business process velocity.

What can we learn from the adoption of artificial intelligence?

The historical record provides insight on the optimal path forward. The “dot-com” bubble is an example of how innovation leads to industry and business change. While falling short of expectations it was a impetus for positive change to come. Many technologies were expected to rapidly change business models and customer experiences during this era, but technology limitations and organizational challenges hindered success. Today, we are assessing these implications for AI adoption.

Today, there are living causes including machine learning applications in the manufacturing, financial services and telecommunications industries. Use of neural networks back propagation models and their predictive modeling power are available and used in risk underwriting, as an example. The current industry excitement around ChatGPT, based on historical language and logic sets, has captured the attention of executives and boards, emphasizing AI‘s potential impact.

Organizations must focus on creating business value through AI, balancing investment and risk. The business and technical requirements and impacts of AI-enabled solutions are not yet fully understood. AI must be effectively governed and managed as any investment would be from the top down. The investment capital, market and business need, and technology capabilities are here today. To remain competitive will require AI adoption.

John T. Weisel, North American Leader at Trask

What are the Board and management AI considerations?

AI presents a myriad of business risk considerations, including competitor risk, customer risk, product and service implications, data protection, and privacy concerns. Marketplace velocity will define AI adoption and its market acceptance and growth. Active engagement by boards and management is paramount.

General approaches for AI governance exist, but must be tailored to each company’s specific strategy, markets and customers, business model, and operating environment. We are observing three primary foci for those organizations most accepting of AI. First, we have observed with several clients a well-structured process for overseeing and guiding AI through effective and enforced board and management policies, procedures and oversight. Second, continuous education about AI‘s implications, answering the what, the why and the how. Lastly, all talent and human capital aspects of AI are considered equal footing with technology considerations.

Technology is no longer the impediment, but rather the enabler of successful AI adoption. Technology costs will increase, but the investment returns will be supernormal.

What are the technology adoption considerations?

Management must actively direct and manage AI use cases. Success is best achieved through simple successful adoption of the higher impact and lower risk use cases. Understanding of internal technical capabilities and requirements, with an understanding all business impacts is essential. These will have a significant impact on business and technology plans and financial implications.

Technology costs will rise in the short term from integration and adoption requirements, but business returns should dwarf these investments. Organizations must reevaluate earnings and capital dynamic impacts, balancing increased technology reliance with a more effective human workforce. An overarching, enterprise-wide perspective on AI is essential.

There is no panacea for successful AI adoption that we have observed across scores of clients. Many third parties assert that they have the solution or services capabilities that are needed. As a 40 year veteran of this industry, I can confirm that this is an embellishment at a minimum. AI as we think about its future today is new. No specific software product, consulting firm nor technology services company has the answers locked. It will be difficult, complex and costly.

The right technical skills and integration and engineering capabilities will be amongst the most important ingredients for adoption success.

How to move forward?

  • Aligning to Business Strategy and Plans - AI should be integral to how organizations think about its business and how to affect change across all dimensions.
  • Embed Governance and Oversight - Implement a governance framework to ensure that AI is deployed effectively with understood and acceptable risks. Use case selection and adoption sequencing and pace are the paramount considerations.
  • View AI as a Portfolio - AI-enabled solutions should be managed as a portfolio, not isolated tests or a pilot program. There are significant synergies often missed.
  • Active Board and Management Engagement - AI must be a standard agenda topic, with an understanding that AI solutions often lack a complete understanding of potential impacts.
  • Embrace this New Era with Caution - Integrating AI into business is an ultra-marathon, not a sprint. Effective governance and management are mandated.
AI demands a thoughtful, structured, and deliberate approach. All will be competing in this metaphorical obstacle race of AI technology adoption and transformation.

John T. Weisel
North American Leader

+1 480 255 4954

John has more than 30 years of global experience in the professional services industry. He has built and led global professional services businesses driving market and client growth, acquiring and developing talent across multiple disciplines, and building world class technology capabilities. His primary domain expertise is in the area of business and technology enabled change.

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