This past June, Fortune Magazine asked all the CEOs of the Fortune 500 what they believed the biggest challenge facing their companies was.
Their biggest concern for 2017: “The rapid pace of technological change” said 73% of those polled, up from 64% in 2016. Cyber security came in only a far second, at 61%, even after all the mega hacks of the past year.
So, what does “technological change” entail? For almost all Fortune 500 CEOs, it means, in part, artificial intelligence. And, as we wrote in our piece yesterday on Forbes.com, “Forget The Hype: What Every Business Leader Needs To Know About Artificial Intelligence Now,” AI is on the lips of almost every global CEO and Board of Directors.
But apart from the Big 8 technology companies – Google, Facebook, Microsoft, Amazon, IBM, Baidu, Tencent, and Alibaba – business leaders, especially of earlier generations, may feel they don’t know enough about AI to make informed decisions.
We made a series of 6 suggestions of how board members and C-suite executives can begin to understand this brave new world of AI, Machine Learning, and Deep Learning. And, after being asked by a number of people to break that list out for them, we include it, slightly modified, here.
- Invest in an initial immersion into AI, Machine Learning, and Deep Learning, and their implications for business — offered as a separate training or tutorial.
- Dive deeply into industry and competitive best practices. You need to take a deep dive into best practices and benchmarks in your industry: what is possible now, what will be possible, what are direct and indirect competitors doing, and what are other industries doing that could translate to your business to give you a leg up?
- Assure you have the right talent on board, across the board. Even in an extremely tight market for AI expertise, leaders need to be asking whether they have the right talent in their organization to make it all happen – because vision and strategy may come from the highest levels of the organization and board, while innovation and implementation will need to be widespread across the organization.
- Assure your efforts are not caught up in silos: AI adoption and projects need to be cross-functional, across leadership levels, collaborative, and informed. They require a synthesis of AI expertise, domain knowledge, business acumen, and corporate strategy and vision.
- Find trusted advisors who you take to, and who can guide you and your AI efforts wisely. Trust and buy-in at the top are hard to marshal in such a fast-evolving technological environment. The need to find trusted advisors to guide next steps — experts who speak your language, and keep pace with AI’s rapid growth as the field reaches and exceeds successive tipping points — has become critical.
- It is imperative to get started, even if you start small. You can start with a proof of concept project to build strategic understanding and successes. Quick wins help bring confidence to technological change. And AI is accelerating — the combination of faster hardware, more data, and new algorithms translates into new models that can be trained in 3 hours, not 30 days. This opens up wholly new applications — those who do not get started now will likely be left behind.
Davia Temin, CEO of leadership and governance strategy firm Temin & Company, helps create, enhance and save reputations at board and executive levels. She is also an Advisor to SpringBoard.ai. Twitter: @DaviaTemin
Bruce Molloy has been an innovator and leader in AI, Machine Learning and Deep Learning for over 20 years. A serial entrepreneur, he has founded multiple AI companies, including SpringBoard.ai
Jayanth Kolla is a strategy consultant to the world’s leading corporations and investors on emerging technologies and digital transformation He is an Advisor to SpringBoard.ai.