AI Transformation: How AI creates real business value
This article explains how AI becomes real business value through the combined impact of models, data, processes, and people. It also highlights process redesign and the growing role of AI agents in day-to-day workflows.
AI Transformation: How AI creates real business value
The speed at which Artificial Intelligence is evolving is gradually shifting the discussion from what models can do to a more essential question for businesses: How does AI translate into real business value?
This was the central theme of the talk “AI in Practice: From Models to Value” by Stelios Iliakis, CEO of Sleed, at the graduation ceremony of the 2nd and 3rd cohorts of the program «AI Transformation: Artificial Intelligence and Business Transformation» of KEDIVIM of the Athens University of Economics and Business.
At the center was an equation that sums up the approach:
Value = Model × Data × Process × People
From AI models to business value
AI models are constantly evolving, while their use is becoming increasingly accessible. In this environment, value for a business is shaped by four interconnected factors:
- Model: the model and its capabilities.
- Data: the data and knowledge the business possesses.
- Process: the processes designed around the new technology.
- People: the people, skills, and new roles required.
The relationship is multiplicative. If one of the four factors doesn’t work, the overall result is impacted as well.
AI Transformation and process redesign
Leveraging AI is directly linked to how the work itself is designed. A typical example is the creation of a monthly performance report.
In an existing process, data is extracted from different platforms, cleaned, charts are created, and AI is used at a partial stage, such as writing the commentary.
In a redesigned flow, data is automatically consolidated, an AI agent creates the first draft and identifies potential deviations, while the specialist focuses on evaluating the insights, discussing them with the client, and the next actions.
In this way, the role gradually shifts from production to evaluation and advisory work.
The role of AI agents
The evolution of AI is taking us from systems that answer questions to systems that can take on specific goals. An AI agent can:
- take a business goal,
- break it down into individual steps,
- use tools, applications, and data,
- check the result,
- repeat an action or hand off the decision to a human.
Under this function lies the context: the knowledge, systems, and information the agent can leverage. Around it are the guardrails: access rights, evaluation mechanisms, and points of human approval.
From AI adoption to AI Transformation
The shift to AI is already affecting different functions of a business: from software and customer service to marketing, finance, and legal. At the same time, real value is tied to how AI is embedded into processes, data, and everyday work.
Technology is only one factor in the equation. AI Transformation requires organized knowledge, workflow redesign, clear control mechanisms, and people who can leverage the new capabilities.
Models are rented. Data, processes and people are yours to build.
