In the age of generative AI, this article, published at the end of 2019 following our IA at Google conference as part of the Verteego Insights, It remains completely up to date on best practices for integrating artificial intelligence into the company strategy and effectively deploying AI within teams!
talenco has been supporting companies in their strategic transformation related to technological disruptions since 2012, and has been raising awareness among its clients about the impacts of AI in society, in their professions, and in their own organizations since 2015.
Artificial intelligence, a deployment that must put the human being at the center
This would have escaped no one; Artificial Intelligence is in full swing. hype with companies.
After creating a buzz among the general public in 2017 with his victory in the game of GO (AlphaGoAfter being at the center of all the events and professional conferences in 2018, Artificial Intelligence is finally – albeit timidly still – making its presence felt in business in 2019.
So why so much caution, or even reluctance, on the part of organizations regarding a technology that all experts assure us is reaching maturity (for the record, the first works of the machine learning date from the late 1950s…)?
In fact, This AI that promises us so many benefits comes with its share of psychological barriers, technological constraints, and, as always during the adoption phase, a lack of feedback..
This results in many statements of intent, announcements of effects, and POCs (Proof of Concept) that end up giving the illusion of going «with the back of a spoon»… an counterproductive impression for its internal acceptance, and a practice that leads to the creation of value in a dispersion of projects.
« Let’s stop succumbing to the POC trend and focus directly on the logic of MVP (Minimum Viable Product) and on things that directly have value… I know of companies where there are more than a hundred POCs underway, of which only about 10% are extended. That represents an incredible cost! »
Jean Baptiste Gouin, CEO of talenco
The real challenge for companies, as in any technological disruption, is to Putting Artificial Intelligence at the service of humanity. Or, the support of leaders (on adapting the strategy), managers (on the benefits of AI) and employees (on the evolution of skills) This is what will require the most resources.
Here is therefore 10 key steps to smoothly integrate Artificial Intelligence into your business strategy and deploy it effectively among your teams.
10 tips for successfully supporting teams in the field of artificial intelligence
1. Assisting leaders in the field of artificial intelligence
There can be no strategic deployment without a clear vision of governance. In the field of Artificial Intelligence, special emphasis must be placed on helping the CODIRs and COMEX to:
- understand this technology (demystify it, and envision its true potential);
- Identify the pain points to which AI can really make a difference;
- give meaning to AI and communicate this vision to employees.
« Let us remember that among the companies with strong growth, 38% of them are implementing an Artificial Intelligence strategy, according to the’Microsoft study published in early 2019!«
Jean Baptiste Gouin, CEO of talenco
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2. Establish a plan to support employees
The integration of a new tool is very often accompanied by a technological deployment plan, in an agile mode. But what plan to accompany the employees on their journey? The evolution of skills in the age of AI ?
It is obviously necessary to be very clear about the targets, deadlines and objectives. A good team support plan provides for the teams’ development and carefully manages communication, as the process will be long and it is therefore essential to keep the employees engaged over the long term.
« To deploy an AI strategy, 50% of efforts must be dedicated to supporting the teams!«
Sébastien Bertrand, Project Director of IBM Watson within the Crédit Mutuel – CIC group
3. Assure employees about the impacts of AI
In October 2019, according to a Oracle study, Only 19% of employees were optimistic about AI worldwide… and even 8% for France! This figure did not necessarily indicate a «resistant» population but rather a minority population’early adopters.
More recently, the global survey AI at Work: What People Are Saying Published in June 2023 by BCG, it revealed that 41% of French employees are concerned about the impact of AI on their jobs.
The challenge today is therefore to quickly shift the company’s focus to a more calm view of what 'artificial intelligence» really is; recent studies proving that many psychological barriers have yet to be overcome.
4. Upgrading teams in AI skills
Today, the concept of skills no longer stops at the technical aspect of a profession or function (hard skills). The digital revolution has changed this. Now, every employee faces the challenge of working in a change of an entire system, This includes understanding the implications as well as mastering the consequences in his day-to-day business practices.
To do this, we usually help our clients, through our generative artificial intelligence training programs, to make their teams understand the importance of this technology. New framework of reality to which they are confronted. This latter consists of 4 pillars :
- technology, of course: everyone needs to understand how AI works, but not just that…
- the evolution of customer behaviors and expectations: the consumer changes with this technology; it is necessary to understand how and to what extent;
- a new one scope competitive: who are the new entrants in your market, their value proposition, their strengths…
- The new societal challenges: no one can ignore the importance of their social and environmental commitment anymore.
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5. Demonstrating the benefits of AI on a continuous basis
To be accepted, any change should be made to give the impression of being wanted rather than imposed. For this to happen, it is necessary to value the concrete and pragmatic benefits that each employee generates over time.
The teams will be more sensitive to this than any other discourse, including one that focuses on a more overall benefit for the organization.
6. Cultivating the feedback Continue on machine learning
This is the very principle of how the system works. machine learning : To improve performance, AI needs to be fed information.. It is on the ground that you will find the necessary material. Therefore, you must create the reflex of feedback, Otherwise, the machine will be poorly trained, therefore less effective, and there will therefore be no benefit for the employee.
But the feedback, This is also the commitment that must be maintained within the team itself, between employees and with management. It is therefore necessary to consider how to value all these commitments on the ground in order to ensure the successful integration of your AI strategy, by systematically «thanking» your employees for them.
7. Valuing human intelligence more than the capabilities of AI
Neuroscience teaches us that humans have a certain ability to seek out, let’s say, doing less of it… Pretending or maintaining the idea that AI could do everything and thus replace humans in all kinds of cognitive tasks would not be conducive to keeping your employees motivated for very long!
8. Don’t talk too much about «artificial» intelligence»
The term has been so exploited for some time, with all the myths that go with it, that it is now overused, and even worse: connoted. To avoid bad interpretations and sterile controversies, it is better to refer – if this is feasible in your organization – to cognitive sciences.
9. Prefering a face-to-face approach to AI
Attention! We must not repeat the same mistake as with the digital acculturation of recent years. Too many companies were misadvised and took a shortcut that cost them dearly in every respect: training in «digital» skills using exclusively digital methods...
All the more reason to be concerned about AI, working on the close-knit relationship Even in the age of teleworking, it is both a factor of reassurance and effectiveness compared to a completely digital or fully AI approach.
10. Pilot the deployment project of your AI strategy
Of course, like any project, The deployment of your AI strategy must be done in an agile manner, It is necessary to adapt constantly. But such a strategic project requires management that knows how to combine long-term vision with very short-term results.
To achieve this, we support our clients with the OKR method (Objectives & Key Results). Attached to the project, these documents ensure that all aspects of the validation process are carried out every 3-4 months. A constant adjustment can then be made based on extremely precise performance indicators, including regarding the organization’s acceptance capacity.
Let us bear in mind that technology is useless if it is not aligned with the human capacity for acceptance.
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