We are approximately four years into the mainstream LLM hype. At this stage a lot of people, company departments and companies have experimented with AI. On the individual level many people have started to understand and see the benefits, but on the company level the benefits are often way more blurry.
This time I invited AI & Data Advisor and our friend Harri from Bruvo to contribute to the topic. Together we share some insights on the situation and how to approach AI calmly and strategically within an organization.
Hype and Buzz
In the Bind
Many decision makers are in trouble with AI and the public discourse around AI does not help at all. LinkedIn is full of anecdotes about the results of using AI, whether it's massive productivity gains, entire products built in days, or various process improvements. Many of these stories are true, but often taken out of context. I’m sure you’ve seen your share of them, so I won’t echo them into the ether again.
Amid all the hype and buzz, company decision-makers feel immense pressure to leverage AI and often worry about falling behind if they haven’t started yet.
Top Leadership
Clear vision and focus
Top leadership must work to identify the most critical points inside the organization where AI should be applied.
As this list often gets long, it also requires a strict prioritization based on the company’s business strategy.
From this, an AI strategy starts to form. And if the company is at their early digitalization steps, this will essentially be a technology strategy with an AI component baked in.
Experimentation
Let people try things out
Clear leadership vision is crucial to be able to define AI experimentation within an organization.
Organization must define a way of experimentation to both guide efforts effectively and gather knowledge.
Ideas often originate throughout the company, and teams need enablement and support for successful AI adoption
Experimentation is needed for successful AI adoption, it just needs to happen under clear leadership vision and enablement.
Upward flow of information
Learnings must go up
This complements the experimentation part; without upward flow if information the learnings from experimentations stay at an individual level.
When people experiment the information must reach leadership too, otherwise the company does not benefit from them.
This upward flow helps adjust top-level priorities.
Better info leads to better tech and AI adoption.
A Final Note
Familiar journey
The journey to use AI efficiently is basically the same one companies already had to take with a broader digitalization, even before the LLM hype . The enablers are in the C-suite, but all personnel must be able to take part in decision making and experimentation.
At Kaiden, we support you with technology advisory and leadership services. Together with Bruvo we can support your journey toward business-aligned data, AI, and the broader technology landscape. Whether you are shaping a full strategy or just exploring where to start, we are ready to help.
Want to hear more? Just book a free consultation call below.
Thanks for reading,
Pyry Kovanen, CEO, CTO in Residence
Kaiden
Harri Julmala, CEO, AI & Data Advisor
Bruvo