maio 08, 2023
Do you ever feel technology and innovation are moving too quickly? Are you worried competitors will adopt new advances in artificial intelligence and get to know your own customers better than you do? Are you using technology and data to differentiate the services that make a difference rather than just the services that keep you afloat?
Running away with the pace
Almost every leader has these moments of worry, but the day job kicks back in, and the focus is once again on the immediate.
That said, the past few months have got some people truly rattled, creating tech anxiety that's more than a fleeting feeling. ChatGPT (or, more widely, generative AI) seems to have come from nowhere and its impact across every industry is growing at an exponential rate.
Even the most confident leaders are now feeling a little bit shaky about the AI revolution, but should they? Or are there bigger problems they should be thinking about?
Understanding our times
The first thing to emphasize is that we are not stepping into the age of artificial intelligence as some may suggest. Instead, this is an era of rapid self-service innovation.
AI is an enabler. Those that make use of it will be the most innovative, agile and nimble of organizations. It's not AI that should have people rattled, it's the small disruptors who already have a foothold in your industry and are able to leverage AI more quickly and to greater effect than you.
Are you ready?
The good news is that the last 10 years of agile and digital transformation have at least set the scene for more nimble and adaptable approaches to change within most organizations.
But time will soon separate the truly agile from those that are agile in name only because the rate at which innovation can take place within the workplace is growing faster than ever and everyone is at it.
So, how can organizations get ready for what's ahead? These are the top three things we think you need to consider:
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Are your teams empowered to experiment with new AI-enabled technologies in an environment where they feel safe to explore and learn?
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Can ideas spread quickly across your organization, allowing value to scale organically?
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Do you have strong data management foundations upon which data can be discovered and utilized safely?
Let’s look at all three more closely.
Empowering innovation at scale
You shouldn't just be thinking about building solutions using generative AI, but preparing for the waves of innovation it will unlock. This includes assessing how easy it is for change to emerge out of your front-line workforce and be adopted at scale.
AI could impact everyone from a shelf picker or truck driver to a till attendant. Will they be able to deal with the introduction of a productivity hack safely? You need to know how to describe the benefit and how to share that idea with perhaps hundreds of people spread across the country or globe that perform a similar role.
We all know that humans aren't always comfortable with change. In many instances, bureaucracy governance and committees will put an almost immediate stop to the cascade of value. But that has to change if you want to stay ahead of the technological disruption that is imminent.
Applying a product mindset
Making sure change is purposeful and user centric doesn’t happen accidentally. We’ve all had an idea we think is great, a new feature for the website or a productivity widget for the daily team huddle. More often than not, these things don’t deliver or fizzle out.
Applying a product mindset to our ideas helps us validate the idea before getting too carried away. It brings user adoption into consideration, and it takes into account the long-term implications of the change. Ultimately, product thinking helps us land change successfully and make it stick.
Building strong data foundations
Your data needs to be discoverable, accessible and trusted if you’re going to make a success of generative AI. That’s because AI is only as good as the data can access.
If a marketing team makes use of an off the shelf AI tool to generate insight, can they really trust that insight if they don't trust the data they are feeding into the engine? The age-old saying "garbage in, garbage out" still applies, and if anything it is even more critical to have oversight of your data than ever before.
It feels obvious to point out that the more data you have quality assured, packaged and shelved for onward use, the more options for innovation you will have readily available at your fingertips. So, while the world gets giddy about generative AI, don’t forget to focus on getting your data foundations sorted in parallel.
The future starts today
We have a right to get excited, experience anxiety and put AI at the top of our agendas. AI will change the world as we know it and it’s happening right now.
Getting ahead isn’t about hiring the top AI talent or investing millions in an AI transformation program. Those that win will create a safe space for experimentation and networks that allow ideas to scale quickly and safely. They’ll get the data foundations right and they’ll remember that AI is going to be as much about people as it is about technology.
