Discover what generative AI will bring for collaboration in the years to come.

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In December 2024, Open AI announced that ChatGPT had more than 300 million users. That is 100 million more than in August, just four months earlier, which represents unprecedented growth. Even the internet had not reached such adoption figures until a decade after its launch (McKinsey).

This interest in artificial intelligence (AI) comes from both consumers and businesses. However, the latter are still struggling to fully integrate it into their operations: Sopra Steria estimates that in 2024, only 22% of large organizations have deployed gen AI on a large scale.

The reason? The rapid and constant evolution of these technologies, where companies need time to set up a structured framework, to upskill their teams to generalize adoption, and to develop real expertise in AI.

By drawing inspiration from early successes in specific areas and applications, we can define key principles for creating an effective and sustainable AI strategy, capable of adapting to future technological developments. This guide offers you 5 steps to develop your AI strategy at scale and realize its potential to improve your efficiency and results.

1. Define your strategic vision of AI

Identify the best use cases

Not all companies benefit from AI in the same way. The first step is to understand concretely if and how AI can improve the activity of each of your company's functions, by asking yourself the following questions:

1. What are the possible use cases?
2. Where will AI add value?
3. What is technically feasible?

It is important to know that generative AI follows a probabilistic model. The answers given by AI-based tools are the ones most likely to be accurate. It will therefore be effective in meeting needs where a margin of error and adjustment is acceptable (writing, repetitive tasks, etc.). However, it will be limited for use that requires an exact response.

Thus, to accurately assess the possible uses, it is essential to take into account the expectations and feedback reported directly by your teams and departments. Feel free to share a quick online survey with them to gather as much information as possible.

Understand the short-term risks

Today, artificial intelligence is still an experimental technology, and has not yet generated a significant ROI for companies. In 2024, according to McKinsey, only 23% of companies believe that AI has helped them reduce their costs, while 43% believe that, on the contrary, it has increased them.

It can therefore be difficult to measure the positive impact of AI in the first months or even years following its deployment. The problem is that this requires a significant initial investment, both financially and in terms of time and collective effort to catch up with this technology.

In addition, there are still uncertainties about the risks of bias, errors and hallucinations committed by AI tools. There is even talk of black box AI, because it is not always easy to understand how AI is trained, and to be able to anticipate all the risks related to cybersecurity and the lack of a current legal framework.

It is therefore important to determine whether deploying AI could present short or medium-term risks for your organization. To help you identify these risks in advance, a tool like the Risk Matrix can help you gain full visibility and adjust your strategic vision if necessary.

2. Think in project mode

Define your resources and objectives

Consider your AI strategy as a large-scale project, for which you need to mobilize resources and set clear objectives. This approach will enable you to move forward in an agile manner by adjusting to changes in the context, while empowering the internal stakeholders involved.

In most cases, companies that equip themselves with AI solutions then adapt them internally to better meet their needs. This means taking into account the time needed for this adaptation, as well as for the recruitment of AI experts, which leads to even larger-scale projects.

In terms of resources, many no-code technologies require no investment in hardware, but you may need it for a customized solution. In this case, the newer and more efficient the technology, the more investment it requires: data centers, computing capacity, etc. Since 2023, NVIDIA has increased its revenue fivefold in its data centers as a result of the demand generated by the implementation of AI by its customers.

Plan the deployment stages

It is important to visualize the major stages of the deployment of your AI strategy now, even if they are likely to evolve later. By doing this alone, you will already have caught up with the vast majority of organizations, as Gartner shows that AI-mature organizations represent only 10% of all those currently testing it.

When it comes to AI, your main objective should be to test continuously in order to adjust and improve.

Start by experimenting on a small scale to better control this process, defining a test team for each identified use case. Get inspired by the principles of design thinking, a methodology that aims to prototype and test a product with a target audience before rolling it out to the entire market.

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3. Build trust in your AI tools

Establish a governance framework

Without trust in your AI tools, there will be no internal adoption. This starts at the stage of choosing the tools, which must be integrated with full knowledge of the facts and aligned with your system to truly facilitate your work instead of being a blockage.

Your priority is therefore to create a governance framework that promotes trust, by providing your teams with secure tools that respect their data:

• Centralize the management of your AI-related processes;
• Communicate regularly with your teams to reassure them and make them aware of your strategy;
• Invite teams to share their feedback, questions and doubts on the subject.

The use of AI must also be monitored to avoid shadow AI, a phenomenon similar to shadow IT. When employees do not have access to internal tools, they may take the initiative to use online AI tools without the approval of their company's technical team. They then risk communicating sensitive information to tools that are not reliable, and which could lead to the leakage of this data.

Take work ethics into account

71% of employees believe that it is up to their employer to establish ethical and secure governance around AI practices (McKinsey). The open and accessible appearance of these tools can indeed raise ethical concerns in your teams, especially if they handle sensitive or confidential data.

Ask yourself the following questions:

• Who in the company has visibility over the data provided to AI tools?
• Is this data used to train AI?
• Who is responsible when confidential data is shared with an AI tool?

From the outset, it is essential to have answers to all these questions. Again, you can find them by asking for continuous feedback from your teams and encouraging open dialogue to actively engage them in the implementation of AI and gradually build their confidence.

4. Promote the adoption of your AI strategy and tools

Whether it is creating the right prompt or integrating AI into your processes to speed up work in a few clicks, adoption at scale requires that you prepare your teams and their managers well.

Align management with team expectations

The difficulties associated with the adoption of artificial intelligence in companies are partly related to a perception paradox between managers and employees:

• On the one hand, managers often emphasize that employees are not ready to adopt AI tools.
• On the other hand, most employees feel they are ready to improve their skills, or even their use of AI. However, they think that their management does not provide them with the resources and access to existing AI functionalities in the tools to do so.

The reason for this? According to a study by Bain & Company issued in 2024, only 9% of companies consider AI to be a top priority topic. More than half (51%) see it as a goal for the next 2 years, and this leads them to de-prioritize actions related to the internal use of AI tools. As a result, employees and middle managers must find other ways to train themselves.

Aligning management with the expectations of the teams is therefore necessary to effectively deploy your AI strategy.

To ensure the long-term adoption of the tools, the best solution is to put the right automatisms in place now. Sometimes all that is needed is to give permission to improve testing or training on a tool with AI capabilities.

Train your teams as much as possible

According to McKinsey, 48% of employees believe that training is crucial in the adoption of AI. However, almost half of them do not receive as much training as they would like.

Moreover, large-scale training programs are difficult to set up because the technology is evolving rapidly, and experts lack the time to structure their training and upgrade their own skills.

One solution to solve this in the short term may be to rely on collective intelligence and encourage your teams to share their best practices with each other:

• During team rituals (monthly, weekly, etc.);
• Through on-the-job training;
• With mentoring from internal experts, etc.

In each case, a collaboration platform such as Klaxoon is ideal for centralizing your ideas, meeting synchronously or sharing information asynchronously, or challenging each other on AI use cases and best practices through gamification.

Understand the impact of AI on your teams

For many business leaders and managers, there is still limited visibility into the impact of AI on employees and their jobs:

• Will AI kill jobs?
• Will it improve employee performance?
• Will it free up time for reflection and creativity?
• Will certain jobs disappear as a result of being automated by AI?

Although it is difficult to get all these answers right now, you can start by taking stock of the current skills of your teams. The main objective is to identify those that are at risk and those that need to be developed, and specific tools such as Klaxoon’s Skills Matrix can help you with this.

You can also use tools like Survey to gather feedback from employees on this subject. In addition, Klaxoon's online whiteboard, Board, also has AI-based features that can help you summarize and categorize the feedback received instantly.

5. Continuously assess and adjust your AI strategy

More than any other project, your AI strategy will be affected by the uncertainties of your context. You need to clearly identify when it will start to generate concrete results for your business, because that is when you will really see what works and be able to make the right decisions for the next steps.

For accurate monitoring, quickly set up KPIs to assess the impact of your AI tools on your results. These can measure:

• Increased productivity;
• Cost reduction;
• Improved quality of deliverables, etc.

In 2025, a major challenge for companies will be to move from testing phases to large-scale deployments of AI. This is when most organizations will begin to see concrete results in the effectiveness of their strategy.

Once you see this impact in your company, it is crucial to use this data to continuously improve your work. This allows you to refine your mastery of the tools, increasing your maturity in AI-related technologies while ensuring that you can quantify the value they add to your business.

Conclusion

According to Sopra Steria, investment in AI by organizations worldwide will increase fivefold by 2028 (from $20 billion in 2024 to $100 billion).

Today, many experts see a disruption similar to that caused by the emergence of the smartphone in 2007. Artificial intelligence will bring new answers to new problems, and some of its applications are still unknown.

For this reason, companies need to adopt an experimental mindset while setting up a framework to ensure the security of their data. It is essential to ensure effective collaboration with tools such as Klaxoon to raise your teams' awareness of AI and help them improve their skills in using, adopting and benefiting from it.

What is certain is that artificial intelligence represents a huge opportunity to increase your efficiency, and by adopting it now in a coherent way, you can ensure that you stay ahead in your market.