The latest rise of AI creates a lot of fears, questions and opportunities. A lot of the discussion revolves around technical capabilities and its direct usage. However, to unleash the capabilities organizations may have to perform more extensive digital transformations. This article reflects upon this topic focusing on the business structures and cultural adaptations organizations should consider. Please do note that given the massive scope of AI it focuses especially on how AI affects the knowledge landscape and what is known today.
What AI currently is and is not
Let’s start by stating that AI is, at the point of writing this article, growing more powerful at a speed that means that some elements of this article risk being old around the date of publication. This and related hype can however blind us to the weaknesses which in turn means we cannot maximize its strengths. So far, AI is primarily information focused, not knowledge nor wisdom focused. It looks at and presents results, yet lacks a deeper understanding (or sometimes any form of understanding) of what it does, if it is valuable or what it can achieve. This makes current AI technology reliant on its userbase, be it a person, team or organization to ensure short- and long-term value.
AI impacts teams on a broad level, not the least the knowledge landscape
Understanding AI’s impact on the organization is of course important to maximize its value. However, it is a topic that can be multiple articles. In short however, even though AI cannot achieve some of its “claims” (yet), it is still offering to transform the very nature of many areas. It can blend into or even disrupt organizations/teams through text, images, videos, code and more. The result, be it an image or entire application, can be impressive.
Nevertheless, the focus of this article is on the knowledge landscape where AI also shows great promise. Let’s take findability and discoverability as two examples. Findability is helped by both aiding the search process but also the information digest through, for example, consolidation and filtering. In addition, discoverability is also aided as areas related to the prompt may be noticed. This enables IT to better serve their organizations and as a result removes some challenges on the IT structural layer. It can also be seen as mitigating some of the pressure on interface/information surface design.
Leaders get stronger, laggards lose out more and non-IT challenges gets even more pressing
On a “meta level”, the short-term development and introduction of AI helps create even greater returns for mature knowledge landscapes/digital workplaces. As a result, it pushes the importance of getting the business structural and cultural components right.
Previously, and to some extent still, some of the value of sharing things, making sure others can understand them, putting in queries to find something and so on was reduced due to challenges inherent in IT. AI can cut these reductions down noticeably. Flipside is that if you are low in maturity regarding your digital workplace you lose out even more!
A curation of challenges and opportunities across intelligence, digitalization, security, business structures and IT
To cover all one must do to reach a well-functioning digital workplace and related knowledge landscape would literally be a small library. However, with the perspective of what is likely coming given the AI developments, some challenges, and “flipside” opportunities worth highlighting are:
- AI still often needs prompts to help you.
You hence need to know what to ask for, or at least which suggested prompt is an effective path towards your goal. Prompting in itself is becoming a valuable skill. - Teams still need to be able to use the right information and turn it into knowledge.
An “unintelligent” team that is solving the wrong problem, using its skills wrong or nor able to utilize its found information is not helped. In fact, they risk lagging behind good teams even more. - AI cannot see what is not digital.
If you have your meetings offline, do not record things, avoid uploading in a shared space, or limit necessary spread of knowledge in other ways, your AI co-worker has trouble. - AI cannot help you if you always just ask someone in the wrong channel.
The not so uncommon culture of simply asking someone to give you information, in a private channel or similar, risks reducing AIs capability to help. It learns less and risks being fed less information. Not to mention that this often needlessly time-consuming element risks being even less effective when the same expert can even more easily share the knowledge with the same effort to the whole organization. - AI does not resolve all challenges with discoverability, interface design etc.
Your information/knowledge surfaces, such as the intranet/portal, is still more than an AI bot. - AI is not the silver bullet for all kinds of lifecycle management challenges.
Getting knowledge into a digital understandable format, managing it over time, securing its long-term ownership and potential deletion is still a critical part of a functional knowledge landscape. - Security efforts are becoming even more important.
For example, creating simple code/applications has been made easier, more quickly finding condensed information can raise risk and social engineering can get even more convincing. However, this only means that creating a strong IT foundation, having properly trained employees, and managing knowledge with a balanced mindset is even more important. - Cheating may not just be a school issue.
Bad unnoticed code, for example, is a problem anywhere. Employees not understanding but simply “applying” information is not necessarily ROI despite the initial appearance. - AI may also not be a simple plug and play.
As so far seems to be the case, AI may need help to “get to know” your knowledge, IT and co-workers. It does help the IT structural layer, but of course also puts new demands on it at the same time.
It is not as easy as flipping a switch. Leveraging AI is about strategy, tactics and operations ranging from IT and business structures to culture across your organization and beyond
To summarize, AI is not a silver bullet to all knowledge problems, it is as much a capability and skill as it is an enabler. As a final piece of this reflection, lets thereby look at some things organizations may be able to do to benefit more from AI in this shape and form:
- Strategy, IT, Business and Culture:
Ensure that across all key value dimensions you secure strategic direction, enabling IT, well-tuned business structure (processes, lifecycle management…) and most importantly culture. - Culture sticks out:
Remember that in the end how people think and act is the key for long term ROI on getting the knowledge you need and capitalizing on it. No matter if we talk about areas such as sharing and finding information, good security or adaptability. - Agile knowledge workstyle:
Learn agility in when to work in real time, non-real time, digital and physical. One does not fit all situations and yet some do not work well with AI! - Collective intelligence:
Make sure your teams function sufficiently to identify the real problem they need to solve, turn information into knowledge and then appropriate results. - AI is powerful, yet dumb:
Remember that AI is a powerful tool, not least for managing information and generating new content, but so far it is “dumb”. - Prepare for the future:
Prepare for the next iterations of AI, both regarding new areas of generating content and being smarter. Having an organization able to adapt, with a strategically chosen maturity for its digital workforce and strong teams is unlikely to hurt!
AI is part of the team
AI is becoming a co-worker. Or more specifically, new AIs are joining your workforce and the workplace needs to adjust. It is an exciting journey which may resemble the massive digital transformations of the past, driving us into a new age. It is also a time where we need to seriously reflect upon where a digital co-worker such as AI best fits relatively to our own strengths and weaknesses. If the pace does not slow down, it is becoming increasingly clear that organizations must find answers and adapt.
