Agentic AI Is Rewriting the Rules of Enterprise Software
The development of artificial intelligence (AI) is transitioning into a new stage with the emergence of agentic AI within corporate IT departments. Unlike conventional AI assistants, agentic systems are capable of planning, reasoning, and autonomously…
The development of artificial intelligence (AI) is transitioning into a new stage with the emergence of agentic AI within corporate IT departments. Unlike conventional AI assistants, agentic systems are capable of planning, reasoning, and autonomously executing complex tasks across digital systems. These systems, composed of networks of specialized software agents, can coordinate workflows, interact with enterprise applications, and make operational decisions with minimal human intervention.
The shift toward agentic AI is driven by advancements in AI models. Large language models have evolved beyond simple text generation to systems capable of multi-step reasoning and structured problem-solving. Current AI systems now score above 80 percent on ARC-AGI reasoning tests, and their performance on complex evaluation benchmarks has improved significantly. The cost of AI inference has decreased by roughly 99 percent over three years. These advancements enable the deployment of AI as teams of autonomous agents collaborating within enterprise environments.
Hyperscalers Build the Agent Infrastructure
Major cloud providers are positioning themselves as central to the agentic AI ecosystem. Microsoft has integrated AI agents into Azure through its OpenAI partnership, allowing developers to embed autonomous reasoning capabilities into enterprise workflows. Amazon Web Services is expanding its generative AI platform, Bedrock, with agent-building capabilities. Google Cloud is following a similar path through Vertex AI and Gemini, targeting enterprise automation use cases.
Enterprise Software Reinvents the Workflow
Enterprise software companies are also incorporating agents into their platforms. Salesforce has introduced Einstein agents for customer interactions and sales workflows. SAP launched Joule, an AI co-pilot integrated into its applications, facilitating complex business processes. ServiceNow is deploying AI agents for IT operations, HR services, and customer support, moving beyond dashboards towards direct process execution by AI agents.
The development of artificial intelligence (AI) is transitioning into a new stage with the emergence of agentic AI within corporate IT departments.
Consulting Firms Face a Structural Disruption
Traditional IT consulting firms face challenges as agentic AI threatens their business model. AI agents can generate code, run tests, monitor systems, and produce analyses, reducing the need for large execution teams. Consulting firms are exploring new delivery models where AI agents handle operational tasks while human experts focus on strategy and governance.
Atos Group and the “Service-as-Software” Model
Atos is pursuing a strategy to evolve toward a “service-as-software” model, where enterprise services are delivered through coordinated AI agents rather than large consulting teams. This could compress project timelines and lower costs, shifting the role of consultants toward strategic oversight.
Control over enterprise data is becoming a decisive advantage for companies experimenting with agentic systems. Autonomous AI agents require constant access to information across various systems. Reliable data access and governance are essential for effective agentic system operations, making the enterprise data platform a critical layer of the AI stack.
Agentic AI is prompting companies to rethink workforce structures. Organizations may evolve toward a model emphasizing highly skilled experts who oversee AI agent networks. This “diamond workforce” model reduces entry-level roles but increases leverage for experienced professionals. Human expertise remains essential for defining objectives, interpreting results, and aligning automated decisions with business strategy.
The next three to five years will be crucial in determining the structure of the AI economy. Cloud providers aim to control the infrastructure where AI agents operate, software vendors seek to embed autonomous intelligence into workflows, and IT services firms work to reinvent delivery models. If successful, agentic AI could transform the enterprise technology landscape, with software agents performing much of the operational work traditionally handled by large human teams.
Based on reporting by TechBullion.