The new era of Artificial Intelligence: what transformations for businesses?

The consultants and partners of Colombus Consulting, Balthazar and Tempo&Co (subsidiaries of the Colombus Consulting group) have gathered the testimonies of 25 players from major groups and AI specialists from different sectors (banking, energy, transport, public sector, luxury) in order to identify the keys to success and the pitfalls to avoid, using examples and best practices.

This white paper presents the perspectives, concrete experiences and challenges of organisations at different stages of maturity and from different industries.

“Whatever the point of view, there is a consensus: major new transformations will take place in the way we work with or because of AI. This affects all areas of the business: general management, HR, marketing, finance, IT, etc.
The main objective is to support companies that want to position themselves as leaders in anever-changing world. AI is not an end in itself, but it represents a powerful lever to rethink, innovate and excel in an increasingly complex ecosystem, where performance and respect for the environment must coexist”, explains Jean Meneveau, Associate Director of Colombus Consulting Switzerland.

The last few years, and especially ithe last few months, have seen an explosion in the integration of AI systems, across all sectors.

This is helping to optimise operational processes, increase efficiency, stimulate innovation and open up new sources of revenue. In fact, the use of artificial intelligence makes it possible to achieve certain results faster and more efficiently, at every level of the value chain and for all the businesses involved.

The success of AI projects lies in the implementation of a clear strategy, based either on a test & learn approach, or on the definition of coherent objectives such as reducing processing time or costs. AI is an opportunity to optimise operational processes, improve efficiency, stimulate innovation and find new sources of growth.

There are numerous use cases for operations, advisers, HR and IT departments.

Companies that have succeeded in quickly launching AI pilot projects have first invested in data work, including governance, pre-processing and data quality, as well as technical architecture. This is an essential, albeit lengthy and costly, prerequisite.

Finally, for companies that are convinced and already operational, the challenges of scaling up should not be underestimated. Firstly, data quality and the implementation of scalable, environmentally-friendly platforms are the cornerstones of successful AI integration. Secondly, the question of AI’s contribution to business value must take precedence over the technology. These considerations must be anticipated and addressed with the utmost care, as they form the basis for the effectiveness and sustainability of the AI solutions deployed.

A consensus is emerging on the need to acculturate and train users in generative AI, while establishing a clear framework for use, to avoid the risks of data leakage and legal implications. Employees must be at the heart of this transformation, as both stakeholders and beneficiaries, to ensure an effective transition to this new era of artificial intelligence. This means putting in place best practices (workshops, videos, tutorials, etc.) to develop their critical view of the results generated by AI, but also to improve decision-making. To achieve this, the first reflex of some organisations has been to draw up a charter for the professional use of public generative AI, to deploy ‘private’ instances based on OpenAI (or other models), or to acquire AI licences integrated into office automation tools such as Copilot.

What’s more, in addition to training on the tool and analysing how it will be used, companies are facing another AI-related issue: its impact on jobs. AI may make it possible to limit certain low-value-added tasks, thereby reducing the number of FTEs (full-time equivalents) needed to performe them and helping employees to move towards higher-value-added tasks.

This is why Human Resources departments, which are at the forefront of the AI revolution, need to immerse themselves in it to gain an in-depth understanding of the transformations to come, particularly in terms of job protection and retraining.

Digital technology accounts for 3 to 4% of global greenhouse gas emissions and 2.5% of the national carbon footprints. As a result, AI raises a number of concerns, particularly about the environment, but also about the role of humans and the new responsibilities they will have. The need to reconcile economic development, innovation and respect for ethical, moral and environmental standards is becoming an imperative in corporate strategy. This is particularly true of mission-driven companies, which have made it a priority.

Some companies have not waited for the AI Act to explore several ways and best practices to integrate ethical criteria into the development of AI. These include setting up internal controls, such as multidisciplinary committees, to assess and monitor the ethical aspects of AI projects, integrating specific criteria into the AI projects evaluation grids, and so on.

This means that certain areas of AI application need to be reviewed at the highest level of the company to ensure alignment with the organisation’s values.

Full White paper