From Chatbots to Agentic AI Productivity Engines
Agentic AI is a model of intelligent software development where AI systems do more than chat: they plan, execute and coordinate multi-step tasks across tools and data sources, under human direction, to speed up complex workflows and raise enterprise software productivity. This shift marks a move from isolated copilots to connected agents that call APIs, invoke services and complete entire workflows in code, data, and operations environments. In agent-based development, engineers and domain experts describe goals and constraints, while AI agents generate code, trigger pipelines, and feed back results for review. The outcome is not only faster enterprise software acceleration, but also AI workflow automation that touches everything from deployment to data quality. Early adopters in travel tech and financial services AI are now reporting concrete multipliers, making it possible to measure return on investment instead of treating AI as an experimental side project.
eDreams ODIGEO: 5x Faster Engineering and 47% More Output
In online travel, eDreams ODIGEO has turned agentic AI into a production engine for software delivery. The company reports that its AI-first engineering model lets technical teams bring new business concepts to market with a five-fold acceleration, transforming innovation cycles across its platform. In its most advanced development teams, 100% of all new code is now AI-generated under human command and design, freeing engineers to focus on high-value initiatives such as complex value-creation projects. According to eDreams ODIGEO, “the AI-first infrastructure has delivered a 47% year-on-year increase in engineering productivity,” a clear sign that agentic AI productivity gains can be quantified at scale. Behind the scenes, more than 100 terabytes of information are ingested each day, while over 100 Model Context Protocol integrations allow AI agents to act on bookings, moving beyond chat into secure transaction fulfilment.
Addepar: Agentic AI Embedded in Financial Workflows
Wealth management platform Addepar is applying agentic AI inside the demanding environment of financial services AI, where data quality and oversight are critical. Building on its native AI experience, Addison, Addepar has previewed AI agents aimed at daily investment workflows. A new data operations agent will help teams find and resolve data issues more efficiently, cutting manual investigation and reconciliation time while improving data quality at scale. At the same time, Addison is gaining broader access to alternatives and private markets data, enhanced visualizations, and more partner integrations, so investment professionals can surface richer portfolio insights and spot risks earlier across the investment lifecycle. New capabilities around Addepar Data Exchange extend AI workflow automation into CRM, cloud data, and business intelligence platforms, helping firms unify and govern information while keeping humans firmly in the loop as decision-makers.
Why Financial Services and Travel Tech Lead Agent-Based Development
Travel tech and financial services are early leaders in agent-based development because they combine complex workflows, strict compliance, and constant pressure for faster innovation. eDreams ODIGEO shows how connecting AI agents to a large booking engine through more than 100 Model Context Protocols turns conversational tools into an additional acquisition and fulfilment channel, completing secure bookings instead of stopping at recommendations. Addepar, by contrast, is weaving agents into operational and analytical layers so that AI workflow automation can clean data, enrich analytics, and tie together front-office and back-office systems. Both cases highlight a pattern: agentic AI productivity gains arrive when AI is embedded directly in core workflows, not bolted on as a separate chatbot. Measurable benefits such as five-fold software engineering acceleration or firm-wide data quality improvements are now setting benchmarks for broader enterprise software acceleration.