What transformations for businesses?

The consultants and Partners of Colombus Consulting, Balthazar and Tempo & Co (subsidiaries of the Colombus Consulting group), collected the testimonies of 25 actors from large companies and AI specialists from different sectors (Banking, Energy, Transportation, Public Sector, Luxury) in order to identify the keys to success and avoid pitfalls with the help of examples and best practices.

“AI is at the center of all the news: media, technological announcements, forecasts of impacts on jobs, questions within management committees, new regulations. Regardless of the point of view, a consensus emerges: new major transformations will occur in the ways of working with or because of AI. This concerns all professions: general management, HR, Marketing, Finance, IT, etc.

In this regard, this white paper presents the visions, concrete experiences and challenges of organizations of various maturities and from different sectors. The main objective is to support companies wishing to position themselves as leaders in a constantly evolving world. AI is not an end in itself, but it represents a powerful lever for rethinking, innovating, and excelling in an increasingly complex ecosystem, where performance and respect for the environment must coexist,” explains GrĂ©gory Garnier, partner at Colombus Consulting.

AI at the heart of strategic and operational transformations

In recent years, and especially in recent months, there has been a real explosion in the integration of AI systems in all sectors.

This promotes the optimization of operational processes, increases efficiency, stimulates innovation, and opens up the possibility of exploring new sources of revenue. Indeed, the use of Artificial Intelligence allows to achieve certain results more quickly and more effectively, at all levels 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 the reduction of processing time or costs. Indeed, AI is an opportunity to optimize operational processes, gain efficiency, stimulate innovation, or find growth relays.

There are many use cases for operations, advisors, HR, and IT departments.

Companies that have successfully launched AI pilot projects have previously invested in work on data, including governance, pre-processing, and data quality, as well as technical architecture. This represents an essential prerequisite, although long and costly.

Finally, for convinced and already operational companies, the challenges related to scaling should not be underestimated. First, the quality of the data and the establishment of evolving and environmentally friendly platforms are the cornerstones of a successful integration of AI. Then, the question of the contribution of AI to business value must take precedence over technology. These reflections must be anticipated and approached with the greatest attention, as they constitute the foundation on which the efficiency and sustainability of deployed AI solutions rest.

Supporting employees in the daily use of AI

There is a consensus on the need to acculturate and train users in generative AI, while establishing a clear framework for its use, to avoid the risks of data leakage and legal implications. Employees must be at the heart of this transformation, both as actors and beneficiaries, to ensure an effective transition to this new era of Artificial Intelligence. This involves implementing best practices (workshops, videos, tutorials, etc.) to develop their critical view of the results generated by AI, but also to improve decision-making. For this, some organizations have had as their first reflex to draw up a charter for the professional use of public generative AIs, to deploy “private” instances based on OpenAI (or other models), or to acquire licenses for AI integrated into office tools such as Copilot.

Furthermore, beyond training in the tool and analysis of its uses, companies are faced with another issue generated by AI: its impact on professions. AI can limit certain low value-added tasks in order to reduce the number of Full-Time Equivalents (FTE) required for their performance and accompany employees towards higher value-added tasks.

This is why Human Resources Directors, on the front lines, must immerse themselves in the AI revolution, to deeply understand the transformations to come, particularly in terms of job protection or retraining.

Conciliating AI and ethics, a major challenge

Digital represents 3 to 4% of greenhouse gas emissions (GHG) worldwide and 2.5% of the national carbon footprint. Therefore, AI raises many concerns, including ecological concerns but also about the place of humans and the new duties that fall upon them. The need to reconcile economic development, innovation, and respect for ethical, moral, and environmental standards appears as an imperative in the strategy of companies. This is particularly the case for mission-driven companies that have made it a priority.

Thus, some companies have not waited for the AI Act to explore several avenues and best practices for integrating ethical criteria into the development of AI. This involves the establishment of internal controls, such as multidisciplinary committees, to assess and monitor the ethical aspects of AI projects, and the integration of specific criteria in the evaluation grids for AI projects, etc.

This means that certain areas of application of AI must be examined at the highest level of the company to ensure alignment with the organization’s values.

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