Stop the Reckless AI Narratives: Why Leaders Need a Practical Strategy & Plan
The headlines that artificial intelligence (AI) is coming for our jobs and even our industries is just — relentless.
It’s the Fiverr CEO’s radical candor to his employees, the Anthropic CEO saying AI will take over engineering, and the countless consulting firm articles predicting the future of work.
From a change management and leadership perspective, I believe these kinds of messages are reckless.
Instead of challenging your teams to figure it out with fear mongering, proactively lead your teams through the strategic adoption of AI.
In fact, when leaders ask teams to adopt AI without strategy and structure, it opens up a ton of risk around duplication of work, intellectual property (IP), personally identifiable information (PII), and cybersecurity.
So, what should we actually do about the pressure to adopt AI?
Hint: There’s more to it than perfecting your latest ChatGPT prompt.
While we have yet to see the future of AI fully unfold, remember that we have in fact charted into the unknown together before — the dawn of the printing press, steam engine, automobile, computers, and the Internet.
Remember circa 1999?
I can still picture the brand new, colorful Macs getting wheeled off to a single room in the school library so that we could take turns learning to type, play Oregon trail, and code terrible websites during a weekly one hour in computer class.
We were told we needed to learn how to use computers for the future of work. And, headlines said the computer was coming for jobs then, too.
Today, computers are an integral part of our education systems, work, and daily experience — right down to the mini computer you keep in your pocket.
They’ve made us more connected, faster, and innovative than ever before. Yet, there’s still an important human component to everything we do.
As a management consultant, I have helped introduce new programs, launch new ways of working, and stood up innovation labs — all creating new roles, processes, and technologies to large organizations.
I’ve also seen the inside of a lot of companies and truth is — while there’s a big hope that companies can leapfrog years-and-years of technical debt, tangled systems, and mismanaged data with AI, most are just not equipped to make that leap.
So, what do we do about talent, operating models, and technology systems in the dawn of this new industrial age?
If I were an enterprise leader today, here’s exactly what I would do to cut through the noise to meaningful action to help teams (real humans) adapt:
First, I’d expand the conversation from AI to hyperautomation to explore a technology stack including AI, machine learning (ML), robotic process automation (RPA), business process management (BPM), low-code/no-code tools, and more for efficiencies:
What processes are automated today?
Which processes could be automated?
Which processes need to be standardized for repeatability for hyperautomation?
Which of our vendor tools have hyperautomation capability that we are using or not using?
Which tools are becoming industry practice with enterprises licenses and security?
I’d further conduct a thorough assessment to get a clear picture of our organization’s current maturity:
What is the team’s current understanding and capabilities around hyperautomation?
What might be some ethical considerations we should consider?
What policies or practices have we documented around appropriate use, ethics, and security of hyperautomation?
What are the costs and benefits of implementing new tools?
What is the current sentiment around hyperautomation at our company for our customers, leaders, talent, partners, and shareholders?
I’d rally a cross-functional team to be creators of the future by organizing a workshop intended to unpack a prioritized set of use cases:
What role does hyperautomation play in our business (e.g., it’s an enabler, it’s our product, it’s who we are as a brand)?
What are the potential use cases (e.g., invoice errors, customer inquiry chatbots) for hyperautomation in our organization?
Which components of our business should always be human?
What would be possible if we had more time to dedicate to new or existing activities?
Where are we today and where do we want to be in 1 to 5 years?
How do we envision roles at our company changing with the use of hyperautomation?
What are the gaps that we need to close in terms of skills, tools, talent, processes, policies to be successful navigating the hyperautomation frontier?
Which low effort and high impact use cases should we prioritize?
I’d create a strategy to ensure that the organization had a clear position on the future structured for enterprise security and growth:
What investments do we want to make for what benefit to our customer experience, talent, competitive edge, and company?
What do we declare will always be human in our business?
What do we see as the capabilities, competencies, and job descriptions of the future?
What technologies meet our enterprise security requirements?
What is our hyperautomation policy (e.g., appropriate use, ethics, security)?
How do our vendor agreements need to change for the use of hyperautomation?
What processes do we need in place to ensure quality review of hyperautomation outputs?
What does the governance of this work look like?
I’d create a plan to implement hyperautomation practices enterprise wide:
What does the program charter and operating model look like to stand this up?
What might be the change impact to roles, processes, and our technology stack?
How do we want to communicate our strategy and policy out to our teams?
What steps can we take to excite and motivate our teams around hyperautomation?
What learning and development programs would benefit our talent?
Which vendor agreements do we need to update?
What types of changes might our teams expect and when?
I’d roll out the programs with immense care to our teams:
Who do we need to roadshow our message to with leaders, teams, and partners?
Who will be our leaders and advocates that can champion key messages?
What feedback do our teams have around the change?
What are some key ways we can iterate, check, and adjust as we go?
How will we measure that the implementation was successful?
There’s no one-size fits all or silver bullet to these questions. Each company must answer them in a way that’s authentic to their vision, mission, products, customers, talent, size, board, and shareholders.
Most companies I see out there are experimenting with no real position or plan.
This may sound like a daunting task on top of leading through a recession, revamping supply chains for tariffs, and marketing to an evolving customer.
This is where we can help.
While AI is new, the motion of standing up new technologies is not. Our team is comprised of early adopters of AI who have led AI-focused workshops, stood up innovation labs, and designed future operating models for all sorts of disruptive technologies.
Set up 15 mins to chat with us about it — for free. Or, email hello@statementco.io.
