AI and data are powerful tools for improving business management, but their adoption remains a huge challenge for executives. Security, ROI, technological integration and digitalisation: our Risk & Smart Data experts help you transform your data into genuine growth drivers and decision-making solutions. Find out all the keys to managing your risks and stay ahead.
Data & AI in businesses: persistent barriers despite proven potential
Although the benefits of data and artificial intelligence (AI) are now recognised by business leaders, their implementation faces many obstacles within companies. According to the latest Data & AI Barometer published by Coface and Les Echos Etudes, 86% of decision-makers now consider it crucial to know how to intelligently exploit data from their clients, prospects and suppliers. This approach is now essential for strengthening the competitiveness and resilience of companies, while opening the way to new growth opportunities.
However, nowadays less than one in five companies leverages on its data to guide its strategic decisions.
This complex reality reveals operational, structural and cultural challenges:
- Profitability: faced with high costs and uncertainty about return on investment (ROI), executives are extremely cautious with their budgets, particularly in SMEs, where the implementation of advanced tools is a significant commitment with no immediate guarantee of results.
- Security and compliance: increasing regulatory requirements, data security and governance, and uncertainties about the use of generative AI are holding back decision-makers, particularly in large companies and sensitive or highly regulated sectors.
- Technological integration: beyond financial and security concerns, the lack of technological maturity in many internal departments complicates the equation for organisations, which point to a lack of time, skills or clear alignment with business priorities.
1- Think bigger... but start small!
Companies that succeed in their Data & AI projects are usually those that opt for a pragmatic approach, starting by targeting concrete use cases rather than rolling out an overly ambitious global strategy. It is better to start with a clearly identified business need and use cases, such as customer risk assessment or monitoring the financial health of a supplier , stock optimisation or fraud detection.
This approach offers many advantages in terms of operational efficiency: results will be faster, more easily measurable and more concrete for business teams. It is a good way to seize business opportunities and gradually optimise your risk management, while strengthening your organisation's data culture before expanding its use to other areas of application, rather than aiming for a comprehensive transformation from the outset.
2- New technologies: implement without complicating existing systems
Regardless of the technological maturity of the teams within your company, a high-performance digital solution must be able to adapt seamlessly to your existing tools and available resources. Whether you are an SME, a mid-market company or a multinational, your needs may differ, but the ultimate goal remains the same: to choose a system that promotes interoperability between technologies without adding additional components to your current system.
Connectivity solutions such as robust APIs, native connectors, and standardised export formats aim to simplify integration with existing business tools without multiplying systems, while preserving previous technological investments and gradually modernising your company's data infrastructure.
3- Make data accessible and actionable
Even the most sophisticated solutions fail if they cannot be translated into concrete actions for end users! Today, accessibility and intuitiveness are just as important (if not more so!) as technological power.
Streamlined dashboards, clear and internationally unified scoring, customisable alerts: the added value of data lies precisely in its ability to be understood, continuously monitored and converted into actionable recommendations. Solutions must be accessible and intuitive in order to interface naturally with teams' workflows and existing processes, facilitating fast and informed decision-making on a daily basis. This user-centric approach ensures the effective adoption of these solutions and maximises their operational impact.
4- Powerful technology + human expertise = a winning combination
What is the difference between a high-performance data solution and a simple statistical tool? Its ability to combine the computing power of AI with the contextual intelligence of business experts. Experience in the field has shown that successful data and AI projects capitalise on both algorithms and human expertise.
AI excels at analysing massive volumes of data, spotting complex patterns and weak signals (like variations in credit scores, sector tension, or a rise in payment incidents). But it's the field expertise that gives meaning and context to the results! By combining ‘the best of both worlds’, smart data itself generates courses of action and thus becomes a decision-making lever. Coface perfectly embodies this dual vision: our Business Information experts transform raw Big Data into exclusive, actionable strategic insights. With the help of descriptive, prescriptive and predictive data, you can anticipate, or even predict, commercial risk and bring confidence to every decision.
Decision-makers are not looking for more data, but for the ability to make decisions faster and with greater certainty. Integrated AI does not replace human analysis: it makes it more accessible, more immediate and more structured.
At Coface, we develop tools that deliver not just raw information, but weak signals, early warnings and contextualised recommendations. This layer of interpretation is essential for transforming data into a real management lever.
- Guillaume Huguet, Director of Coface's Data Lab.
5 – Measure added value
By definition, a project based on data and artificial intelligence cannot be frozen in time. It is constantly evolving, depending on the needs of the company, market developments and the enrichment of available data. This requires the implementation of precise and regularly measured performance indicators (KPIs).
ROI, adoption rate, prediction accuracy, risk reduction: these are all indicators that will be real performance drivers for your company. These metrics not only give you greater agility in managing your project according to current priorities, but also allow you to demonstrate the added value of a data-driven strategy to your stakeholders. This continuous measurement of added value is the best guarantee of a successful and sustainable technological investment.
Go further with Coface Business Information
For many years, the Coface Business Information teams have been supporting companies of all sizes, all over the world, in the roll-out of commercial risk management solutions based on data and artificial intelligence. Because acting means anticipating, you too can transform your data into decision-making tools.
Discover our Business Information solutions and contact our experts near you for a customised demo.
