AI Adoption: Constellations, Not North Stars

Posted by Neil Sheppard on May 16, 2024
AI Adoption: Constellations, Not North Stars

Generative AI adoption is not a straight path and putting all your eggs in one basket may not be the right choice. Find out how you can leverage a variety of AI strategies to mitigate your risk.

Industry commentators are calling for clear strategies for leveraging artificial intelligence (AI) for enterprise. Yet, while clarity is important, limiting yourself to adopting just one AI solution is a tremendous risk.

The simple truth is that none of us understands how best to utilize this brand-new technology just yet. As such, it's best to keep your options open rather than rolling the dice and hoping your AI strategy turns out for the best.

This doesn't mean you should hold back from leveraging AI technology, however. Avoiding AI is, itself, a single strategy that might not pay off.

The way forward with AI adoption is to court several different AI strategies, without fully committing or risking vendor lock-in. Then, when the fog lifts and the future of business AI becomes clear, you'll be in the best position to drive forward.

The key to keeping your organization AI agnostic is to have full oversight on the AI solutions that are in-use throughout your company. To do that, you need an application portfolio management solution with dedicated AI functionality, like LeanIX:

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Lost In The AI Fog

Forrester believes that generative artificial intelligence (AI) will be as transformative as the internet, the smartphone, and social media. Just as none of us could have predicted the rise of Netflix, Uber, Door Dash, or TikTok, it's impossible to predict where AI will take us in the future.

This is putting tremendous pressure on IT leaders. Laggards in AI adoption risk being left far behind by the competition, while early adopters face falling on a scale somewhere between simple vendor lock-in and pivoting their entire business model towards a product that will cease to exist in two years' time.

It's like being lost in a fog and knowing taking a step in any direction could also be one over the edge of a cliff. IT leaders are, therefore, being called on to give their businesses a clear direction to proceed in when it comes to AI.

This is why companies from Dropbox to Deloitte are calling for decisive action on AI. The recommendation here is to choose a "north star metric" - a key goal that will guide your AI strategy wherever the market turns.

Sticking with our 'lost in the fog' metaphor, this is essentially just picking a direction, walking that way confidently, and hoping it's the right one. This is a great strategy for overcoming 'analysis paralysis', but it's also placing the future of your business in the hands of lady luck.


Is An AI "North Star" Really The Right Strategy?

This is a common strategy when it comes to complex situations. Not taking action will often lead to a worse outcome than making a mistake, so it's best to just do something, rather than run out of time trying to work out the right thing to do.

A common business metaphor around the time of the 9/11 terrorist attacks was that, if you were in the Twin Towers with a plane flying towards you, it would be better to jump out a window and figure out how to survive as you fall than to stay put. The appropriateness of the metaphor aside, this is simply bad advice as jumping out of the window would ensure you didn't survive.

When taking no action would lead to certain doom, taking a risk on a random action loses you nothing, but that isn't the situation with artificial intelligence (AI). Being tentative about AI adoption could cause you to lag behind in the market, but locking yourself into the wrong strategy could be far worse.

Of course, choosing a single north star metric doesn't necessarily mean locking yourself into one strategy. What if you choose the wrong metric, though?

What if your north star metric is internal net promoter score (NPS), but in the future we realize AI is best leveraged for automated, behind-the-scenes processes that most people in your business are completely unaware of? You could be locked into an expensive and ultimately useless AI onboarding tool, when you really should have been investing in using generative AI to monitor your team's social media use.

Since we really don't know what the best-practice use case for generative AI will turn out to be, we're currently better off experimenting with the technology in several use cases and seeing what turns out best. By starting out with a minimum viable use case for AI and iterating and increasing our investment as we find what works for our organizations, we ensure we're not locking ourselves into the wrong strategy.


AI Constellations, Not North Stars

Rather than focusing on a single north star metric, start tracking the potential use cases for generative artificial intelligence (AI). Derive a set of metrics for each and track them within categories.

Of course, you need to ensure that your employees aren't using AI in ways that will cause security or reputational risks, such as when Samsung caught employees uploading proprietary code into ChatGPT. However, it's worth allowing employees to test out AI solutions in safe sandbox environments to discover their value.

When the metrics for an experiment start to look impressive, increase investment in the tool. When a certain use case has been explored and isn't offering a return on investment, then end the experiment with that tool until another use case arises.

This is, of course, more effort than simply committing to an AI strategy that feels right, and you will need to carefully limit your investment so the costs don't add up. However, by diversifying your AI adoption strategy, you gain empirical evidence of what AI tools have value to your organization.

By remaining agnostic about AI, developing business use cases, and taking tentative steps forward with tools that offer real value, rather than jumping in with both feet, you can gain all the value that AI promises without exposing yourself to potentially devastating risks. This is the only safe strategy for leveraging AI, as even refusing to implement AI tools could have consequences in the long term.


Leveraging LeanIX For AI Adoption

The LeanIX Application Portfolio Management product empowers you to store all your vital information regarding artificial intelligence (AI) software within a single repository. From here, you can log a range of metrics in customized dashboards that can be shared with all your stakeholders.

Using the LeanIX Architecture and Road Map Planning solution, you can then experiment with this data in a sandbox environment to see what potential changes could drive your infrastructure forward. Once you have a vision for the future, you can then map a path from where you are to where you want to be.

To find out more about how LeanIX products can support your AI adoption journey, book a demo: 

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