CxOs need to heed the lessons of cloud transformation when dealing with AI

CIOs and other executives need to be ready for another major change imperative in the form of AI… but what can they glean from past events? Smart leaders will learn from history and apply key lessons from the last landmark technology-enabled inflexion point: cloud computing and the rise of ecommerce.

I’m old enough to have lived through the cloud computing revolution and it was a remarkable time. The changes to the way we deployed and ran IT had significant impacts internally (elastic capacity, lower upfront costs, a smaller admin overhead, reduced ‘shelfware’) but also on broader business performance.

Cloud computing accelerated decision-making and lowered the risk and expenses associated with R&D and program and process trials. I believe that AI will be even more transformational and drive more impact, especially on the business side.

Let’s be honest here: all major change exercises have bumps on the road. Cloud certainly did and AI tools will not be an exception to that rule. Those who went through cloud-enabled business transformation, as I did at Accenture, need to apply wisdom, recognize familiar obstacles and opportunities, and act accordingly.

An incomplete shortlist of concerns will include:

- securing buy-in from stakeholders;

- managing up, across and down, including scope for retraining and new roles;

- not buying into propaganda or ‘tulip mania’ where hype exceeds reality and common sense;

- avoiding vendor/platform lock-in that restricts downstream flexibility;

- building necessary and complementary skills and partnerships externally;

- managing new vendors with new tariff structures or ways of working;

- re-engineering business processes to capitalize on technology change;

- and seeing this as a holistic change opportunity, not a technology silver bullet.

Let’s dive deeper into a few of these…

Understanding limitations

It’s OK not to know everything. In business, we do everything we can to look ahead, see around corners and anticipate next steps. But ultimately we rely in part on best guesses. That’s especially so in the case of AI (or cloud), the underlying technology is moving very fast. There’s nothing wrong with making incremental changes to plans and course-correcting on a regular basis. And, as goalposts inevitably move, it’s the only sensible approach.

It may get worse before it gets better. Any big change program carries risks. With cloud, we made mistakes that led to unexpected consequences like cost spikes and ‘bill shock.’ We didn’t always factor in what we would consume and how much that consumption level would cost so results sometimes got worse in the short term.

But everything we can know today tells us that investing in AI is a strategic competitive advantage. Some projects will fail and computing costs may come with a higher price tag, but these are short-term challenges that will ultimately lead to long-term progress and our ability to innovate, automate and analyze.

First-mover advantage isn’t always an advantage. In the cloud, there was industry, media and peer pressure to adopt quickly. We feared laggard status and missing out on a promised competitive advantage. Later, some former ‘laggards’ claimed a ‘second-mover advantage’ because they observed the frenzied action before reacting.

The truth of what was better (first-mover or second-mover) was somewhere in the middle. Some sectors and organizations moved fast successfully, while others were better off once the dust settled. There were significant variances caused by differences in industry, company profile, skills and risk appetite. Establish which camps you fall into to move at the right speed but make sure you are prepared to make big moves when the time is right.

Rethinking security and governance

Security and governance need a rethink. Many people underestimated the impacts on data privacy and regulatory compliance in the cloud. This led to cybersecurity compromises caused by misconfigurations and external risks due to the larger attack surface that was presented.

With AI, we need to accept that immense new power will also be used by malicious actors so we must mitigate risks caused by new processes and well-meaning employees and partners.

Vendor choice is different. New technology waves bring new vendors. Smart CIOs will look at the risk of using untested providers, analyze their backgrounds and likely futures, and make choices accordingly.

They will often be assisted by chief risk officers, identity, privacy and sovereignty experts, change veterans, and others with specialist domain expertise. Organizations must avoid being locked into vendors or platforms that restrict downstream movement and value.

Business process change is more important than technology change. Change can’t sit in an IT silo. It’s more important to understand new vistas of possibility and rethinking what business processes are ripe for AI-enabled change. Just as important is communication. So winning buy-in from above, below and across the organization is critical.

AI is exciting, fast-moving and, yes, scary. It’s fine not to get everything right but learning from history will help.

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