If your LinkedIn flow is like mine, 80% of the content spokes about how the latest model of AI will revolutionize their business. But for me, it counts almost zero – people fell it. The thing that will determine the most important thing to what extent one company will benefit from AI is their culture – it is a change in change management, not a problem of using this model of AI or that.
More specifically, it is a change management opportunity. It is an exciting period of history when people at all levels can be autonomous by technological changes – and you, as a business manager, can be the one that motivates your organization and helps to browse this change process successfully. To do this, I found it means to come back to the essentials.
My own “bases” include a diploma in psychology well before starting to build AI products, and I got more and more from fundamental psychological concepts to generate better results as customers with whom I work adopt AI in their business. Here are the principles of change management which can also allow your organization to transform the AI.
Transform uncertainty into understanding
One of the biggest obstacles faced by organizations implementing AI is fear. The fear of needing new skills, of innovating faster than you can follow, and especially the AI ​​making the roles redundant – all this is understandable and is worth a huge empathy. But concerning-The lift itself to the way these feelings with regard to AI are presented and are conceptualized for future success.
Like the School of positive psychology has established, human concerns need a human approach: more than simply alleviating negative emotions, it is more effective to focus on forces, well-being and growth. In other words, passing your mail from pathology to compassion, from pessimism to optimism, is the only way to resolve very real fears And Get real membership in new ways of thinking.
I honestly believe that the most effective communication strategy is now to put In the context of previous points like the industrial revolution or the start of the Internet. It is unpredictable, but it is exciting: people acquire new skills and acquire new things that no one on earth has never done before. Your real passion for doing new things and making real progress on the scale of society will be the basis of a corporate culture that embraces experimentation without fear and with enthusiasm – to set the tone for all the transformation efforts of the following IA that your team undertakes.
The most underestimated link in AI adoption
These efforts, however, will have to rely on your positive corporate culture by entering nuts and bolts from the way individuals learn new skills and habits. Giving your business the basic skills that everyone needs in the AI ​​age cannot simply be a powerpoint; Measuring results cannot be an investigation. Your adoption plan must be a long -term extensive initiative motivated by observation learning and the expression of conditioning principles.
Familiarity generates contentment
Observational learning Social learning is how children at the head of athletes model behavior according to what they have already seen. In other words, show me things I can identify with, and I will adapt-maybe not perfectly, but comfortably. As human beings, we are designed to work in this way.
This is how our company, DoBuild our internal AI adoption program. We have sent a detailed questionnaire to each employee – What tools do you already know? What are the pains you would like to approach? Who are you already coming from with questions about AI? The responses constituted the basis of the tailor -made learning plans individually, giving each member of the team an exploitable roadmap to develop useful AI skills in a familiar manner.
From the concept to the habit: Bâton on AI
Ensuring the rooting skills really requires a real value of the learner. For this, AI must be anchored in existing tools and processes – it cannot be a heavy “distinct thing”. For example, the capabilities of the integrated AI in Slack can do wonders to complete my reflection and maximize the results in an application where I already spend my time.
In the end, the identification of the place where the AI ​​will produce the most value must be determined by the way in which the specific roles see maximum conviviality – giving everyone the latitude to identify the individual bottlenecks and the skills in AI to resolve them, alone or in collaboration. This positive will confirm the thought that AI actually Let yourself perform tasks faster, better or completely new.
Showing this value in daily processes constantly will go even further: over time, Classic packaging Will automatically make the mind AI each time a complex or unknown task must be resolved.
Trust but check
AI agents should be essential tools, but they cannot work on the automatic pilot; Ais citing nonexistent legal affairs Or The columnists recommended false books There are two recent examples of the risks that completely accompany the human element. Assess the risk appetite for each The use of AI is crucial to implement the best solution.
However, as any parent of a teenager can assure you, humans are delivered with integrated unconscious biases that make the risk assessment with precision. THE heuristic availabilityFor example, we push us to overestimate the probability of particularly memorable events; its quasi-opposed, the Optimism biasleads us to believe that negative events are less likely to happen to us than to others. And these are only two of one Very long list.
The tools that help you check the results of your AI agents and orchestrate how they operate together is a step towards reduction of prejudices and risk management, and avant-garde IA companies develop them. But knowing what bias exist first and how they work, it will be the way you give meaning to the problems that appear and save against them.
Conclusion
In the end, navigating in the transformation of the AI ​​will not be very different from the digital transformation that many of us have already lived. As we have noticed then, getting out better, faster and stronger means controlling the principles of changing low technology change: understanding how the human mind will work will help us to adapt – and make the most of – this new courageous world.
Darin is vice-president of market strategy at Make. It highlights Make's late innovations to keep customers at the forefront of automation and agility of the workplace, and before the Make Make product team.
In addition to its product expertise, Darin is deeply interested in the way technology and operations can be deployed for social good, having worked with a wide range of health providers and human services to maximize their impact.
