Transformation of Investment Jobs through Artificial Intelligence
The panel "Sourcing & Due Diligence 2.0" at the annual conference of the Tunisian Association of Venture Capitalists (ATIC) explored the profound transformation of investment jobs under the influence of artificial intelligence. Between data exploitation, weak signal detection, and process automation, experts outlined the contours of a new paradigm where decision-making becomes more predictive, continuous, and enhanced.
The Data, a New Strategic Asset for Investment
According to Louay Salti, Head of Product at Axe Finance, traditional decision-making models are now reaching their limits due to the increasing complexity and volume of data. Data is no longer solely internal to financial institutions; it now comes from multiple external sources, often unstructured, from various digital ecosystems. This evolution requires data structuring and normalization to transform these flows into exploitable signals. These signals then feed into scoring systems and decision-support tools, allowing for a shift from descriptive analysis to predictive logic. Generative artificial intelligence accelerates this movement by automating the extraction, analysis, and synthesis of financial and non-financial information.
Due Diligence, a Central Strategic Exercise
In an unstable economic context and faced with increasingly complex business models, Nejla Mejri Ep Hedriche, a partner at Deloitte, emphasizes that due diligence has become a central strategic exercise. It is no longer limited to financial and tax analysis but now integrates legal, social, environmental, and technological dimensions, including cybersecurity. Artificial intelligence enables a more exhaustive analysis of data, particularly from data rooms, while improving the detection of inconsistencies and sectoral benchmarking. This contributes to faster and more accurate analyses. However, this transformation comes with a requirement for transparency: the majority of investors support the use of AI, provided that the final decision remains human and fully responsible.
A Profound Structural Transformation of Venture Capital
For Anis Laadhar, a partner at EY Parthenon, venture capital is undergoing a profound structural transformation. Sourcing no longer relies solely on relational networks but on intelligent agent systems capable of continuously analyzing massive amounts of data. The role of consulting is also evolving; it is no longer just about making connections but about designing analysis frameworks and "investment rules" that allow for the industrialization of opportunity detection. In this model, weak signals become central: accelerated recruitments, changes in governance, or the arrival of senior profiles are interpreted as advanced indicators of transformation. AI also enables the personalization of commercial approaches based on identified profiles.
Towards Continuous Vigilance of Investments
For Haikel Drine, CEO of Afrikanda, artificial intelligence marks the transition from a punctual due diligence logic to a "continuous diligence" approach. Company monitoring becomes permanent, automated, and based on real-time data flows. This evolution allows for earlier identification of opportunities and better anticipation of market dynamics. However, this transformation comes with significant challenges: data security, team training, and ethical responsibility. While AI automates many tasks, the final decision and strategic contextualization remain human.
Adoption of AI in Venture Capital, Still Limited
The adoption of AI in venture capital remains limited, hindered by budget constraints and poorly structured governance. Most players do not yet see immediate value, even though uses focus on process optimization and data analysis. Beyond tools, participants highlight a profound change: AI transforms the job without replacing humans, who remain responsible for decisions. The challenge is no longer the technology itself but its proper integration into investment strategies.
