Remaining Mindful in the Age of AI

Authored By:

Geir Arnhoff, CEO of Dossier

Geir Arnhoff


Remaining Mindful in the Age of AI

I have had so much joy the past year with all the new large language models (LLMs) and Generative AI becoming a commodity. Still, I shift between euphoria and FOMO almost every second day, just as a result of everything new being released, published, and talked about.

Last week, I had the pleasure of participating in a panel discussion with a few people I admire for their deep insight and broad perspectives: Jeff Trost at Laerdal Million Lives Fund, Amar Dixit at San Mateo Medical Center, and Scott Barclay at Insight Partners. Our discussion was part of the California Norway Business Festival in San Francisco. The conversation encouraged me to share our perspectives on AI within Dossier.

We Can Never Say This Enough

Regardless of any technology or solution you have put together, if it’s not helping your customer solve a problem faster, quicker, and cheaper than before, you have most likely lost focus. And if the problem “just exists” without being solved in a more complex, more cumbersome, and more expensive way today than what you can do, then the problem is most likely not a big enough problem to address. 

Of course, there are nuances, such as the creation of the iPad or any other consumer category that is “creating its own needs.” However, for any B2B business, we have to focus on the problem of making any adaptable technology available. That means a technology the customer is capable of implementing and leveraging. 

I bring this up in relation to AI because, with AI, it’s easy to be over-enthusiastic about the potential capabilities so much that the fascination with advancement possibilities derails us from creating something that’s in the adoption span for our customers. Because any adoption of new technology requires a change in workflow by the customer, we need to ensure the innovation meets the customer’s capacity for change.

Magical Building Blocks

Making software is not so far from building blocks. Start with a goal in mind, then create some design mock-ups based on what you think is possible to make with the available building blocks. Then start to build. 

Often, with an MVP (minimum viable product), show it to customers, have them try using it, gather feedback, and then start the iterative improvement process. With LLM (aka AI), almost out of the blue, we have a whole new range of supercharged building blocks available. As long as we can integrate these blocks into our existing systems, they can accelerate development and bring unprecedented functionalities to our solutions, making them more robust and versatile.

Pack Light, be ready to jump over to the faster train

In an age where technology evolves at breakneck speeds, it’s crucial to remain agile and adaptable. Packing light in this context means avoiding heavy dependencies that could slow down our ability to switch to more efficient technologies as they emerge. 

This agility allows us to overcome the release of anxiety often associated with frequent and rapid technological changes, ensuring we’re always at the forefront of innovation. Even worse than being lost at the train station, unable to catch the train, is being stuck on a slow-moving train, seeing your competitors racing away with the high-speed train that became available after you invested too heavily in the steam locomotive train tickets. In the age of rapidly emerging technologies, it is crucial to “pack light” and stay agile to jump to the better technology becoming available.

AI and LLMs are, for us, commodity

There are a few companies that actually create LLMs and AI. The rest of us benefit from those technologies becoming available as commodities. We need to monitor and remain in control of future dependencies. 

Building your application on top of other applications can result in risks. For example, you could sacrifice your financial position by losing control of your technology’s future costs. The shift from OpenAI to “ClosedAI” is just one example of the importance of securing future predictability and staying agile.

Take away

It’s vital to control future dependencies. As technology leaders, we need to ensure that while we embrace these powerful tools, we also safeguard our ability to innovate and adapt independently, ensuring our business remains robust, flexible, and competitive.

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