When Data Speaks: AI Agents Are Transforming Managerial Decision-Making
AI agents are changing how organizations handle information: managers are moving from static reports to real-time dialogues with data, enabling them to gain insights and trigger actions directly within corporate systems.
If in the past managers made decisions based on reports produced once a day or once a week, today they are approaching a new reality where organizational data becomes an active partner in the decision-making process. Instead of searching for data on dashboards, opening Excel sheets, or requesting reports from analytics teams, they can simply ask a question in natural language and receive an immediate, data-driven answer, and even trigger an action within the organizational systems.
This change is part of the broader shift to the era of the "Agentic Enterprise" — an organization where AI agents do not just provide information, but understand context, collaborate with employees, and perform tasks autonomously under defined permissions.
From Traditional BI to Conversation with Data
BI systems have changed how organizations analyze business information over the years, but they still required the user to know where the data is and how to interpret it. Managers were required to navigate between dashboards, define filters, and sometimes wait for data updates.
AI agents add a completely new layer. They allow for a dialogue with organizational information in natural language, understanding complex questions, performing cross-referencing between different data sources, and presenting insights in real-time. In many cases, they are also able to continue the conversation, remember the context, and suggest operational steps.
The Agentic Enterprise Is Already Here
The Agentic Enterprise is the next stage in organizational evolution. A model where AI agents become an active part of workflows and help employees and managers perform tasks, analyze information, and make decisions. Unlike traditional AI tools that perform point tasks, smart agents are able to understand context, connect to organizational systems, act according to defined permissions, and even perform a sequence of actions independently.
One of the companies leading this trend is Salesforce. "In the Agentic Enterprise, AI agents are not just another tool in the employees' toolbox; they become digital partners that help organizations operate in a smarter, faster, and more adapted way," notes Itai Margalit, Regional Vice President and Head of Business Operations at Salesforce Israel. "The value is created when the agents are connected to organizational data, understand the business context, and work alongside employees to improve processes and results."
In this context, the company introduced the "Manager Agent," an AI agent that assists managers in daily tasks, from analyzing employee survey results to recommending actions for performance reviews.
When Information Moves to Voice
Parallel to the development of AI agents, another revolution is taking place: the transition from text-based to voice interfaces. A voice agent adds another layer of interaction, allowing for a natural conversation with the system, maintaining context, and performing actions via voice command.
Companies ONE datAI from the ONE Technologies group and Tokomni.AI recently launched "Talk 2 Your Data." The solution turns data into an Executive Agent, connected directly to organizational sources such as email, calendars, and WhatsApp, allowing managers to receive answers and perform actions using speech only.
According to Ofir Isaac, CEO of ONE datAI: "The next stage in the world of data is a transition from consuming information to working together with information. The ability to talk to data in a natural way changes the work experience of managers. It allows turning information that existed in the organization's systems into available insights, anytime and anywhere."
From Dashboards to Conversation: What Is Required to Work
Oz Nevo, Partner and Lead of Data & AI at Deloitte Israel, believes that the transition to AI agents is not just a change in the user interface, but a change in how organizations derive value from their data.
"The traditional dashboard has reached its capacity limit. It only answers questions that were planned in advance. This is where 'Talk-To-Your-Data' systems based on language models come in: the user asks a question in free language, the system interprets it, generates a query, runs it, verifies it, and returns an explained answer.
"However, it is important to emphasize several aspects. First, governance and security must apply to the agent exactly as they apply to a human. Second, accuracy must be measured. Teams need evaluation mechanisms, automatic verification of generated queries, and a Human-in-the-Loop for actions with consequences. Third, cost, performance, and infrastructure of the semantic data layer are engineering realities that must be planned in advance."
Author — Ili Ben Haim, HR Manager, Salesforce Israel.
