Software is at an inflection point.
For most of its history, enterprise software worked on a simple arrangement: vendors built monolithic applications with functionality locked inside user interfaces. If you couldn't click to it, you couldn't get to it. That arrangement made sense when humans were the only ones doing the work, but as AI has matured from a novelty to a genuine operational capability, that model has started to break down.
For years, the SaaS industry asked: where can we infuse AI? The answer was predictable. Add a chat interface here or an AI-assisted button there. It was intelligence bolted onto the existing structure. That approach preserved the old constraints of siloed systems, rigid workflows, and human-executed steps. It gave the impression of change without the substance of it.
The question that matters today is different: how can AI use the software we've already built? That's the crux of how SaaS companies can enable an agentic enterprise, and it demands a fundamentally different kind of software.
What changes when AI acts.
The shift happening now is moving away from AI that merely advises and towards AI that takes action. It’s not just happening in martech – it's across the board, and it's architectural, meaning the way enterprise software is built needs to change to support it.
Consider what happens today when a competitor undercuts your price. Someone notices. They alert the team, schedule a meeting, debate the response. Then, briefs get written, campaigns are built, and your team starts chasing approvals over the next several days. And by the time you launch…customers have moved on.
With AI integrated into your workflow, tomorrow looks different. An agent can monitor market signals continuously by tracking competitor pricing, inventory changes, and customer behavior in real time. When it detects the price cut, it immediately identifies at-risk customers, drafts a retention offer, and simulates outcomes—then routes any briefs or requests to the right stakeholders. In a matter of hours, your marketing team is ready to launch. The whole sequence, from signal to live campaign, moves significantly faster because everything between the decisions is now automatic.
Perhaps even more impactful, however, is that the agent doesn’t stop working after the campaign launches. As customers respond to the campaign, the agent captures customer signals, analyzes performance, and surfaces recommendations to your team—adjusting audiences, content, and creative along the way to maintain engagement. What started as a response to a single price cut becomes an ongoing customer engagement strategy that learns and adapts over time.
Architecture designed for machine speed.
The platforms that enable this type of future share a common characteristic: they've opened themselves to AI. Not by adding an AI layer on top, but by rebuilding from the ground up. Decomposing monolithic applications into fine-grained, composable capabilities that AI can discover, invoke, and orchestrate. Your data, models, services, and business logic become available not just to your teams by clicking through a UI, but to agents operating across your entire technology stack.
This is what we call the composable AI fabric: open, flexible, and autonomous. Open because capabilities are directly accessible via protocols like MCP, discoverable by any agent from any entry point, flexible because LLMs become universal connectors, stitching capabilities and orchestrating actions iin ways no one pre-designed. And finally, autonomous because AI operates and humans govern, rather than the other way around.
Adobe CX Enterprise Coworker is where this new architecture becomes operational.
Introducing Adobe CX Enterprise Coworker.
Adobe CX Enterprise Coworker orchestrates customer experience workflows across your enterprise marketing systems. Drawing from the Adobe systems you already use, it understands your business context from day one and remembers new information across sessions. It governs itself within your policy boundaries and executes complex multi-system workflows while checking in at the moments that you define.
How your team works with Adobe Coworker depends on what they need. Practitioners with day-to-day questions and one-off tasks work through Coworker Chat, handling complex requests through natural language — pulling insights, generating content, and taking action across Adobe applications without switching context. Agile marketing teams that need to move fast use Coworker Campaigns to go from goal to live campaign in a fraction of the time, with on-brand assets, a recommended campaign structure, and coordinated execution built in. And for enterprise teams managing complex, cross-functional workflows, Coworker Projects brings everything into one place — letting teams define their own workflows, set approval checkpoints, and determine exactly how much autonomy Adobe Coworker has at each stage. Work keeps moving without anyone losing visibility or control.
Behind each module is a set of capabilities built for the demands of enterprise, where governance, memory, and business context aren't optional extras but the foundation everything runs on.
The six capabilities of Adobe CX Enterprise Coworker.
Adobe Coworker is composed of six modular capabilities that work together to make agentic AI practical for enterprise customer experience teams.
1. Business taxonomy. Pre-loaded from your Adobe applications at onboarding, Adobe Coworker includes audience definitions, campaign logic, brand taxonomy, and journey designs. It can also extend into CRMs and data warehouses or data lakes for a complete operational picture.
2. Governance. Adobe Coworker automatically inherits roles, permissions, data policies, and brand guidelines from other Adobe applications. These can be supplemented with approval workflows, compliance requirements, and access controls from enterprise systems.
3. Long-term memory. Business context is retained and reused across sessions, agents, and team members. What Adobe Coworker knows can also be enriched with campaign performance history, customer interaction records, and business outcomes from connected enterprise systems.
4. Agentic skills. Adobe Coworker understands how to operate across the full scope of customer experience work — audiences, journeys, content, and insights — and knows which capabilities to invoke and how to sequence them to get the job done. It can also extend into your own tools and integrations via the MCP registry.
5. Agentic workflow builder. Define business processes using natural language. Teams can specify goals, approval checkpoints, and the desired autonomy level for Adobe Coworker. They can also determine if sequences should be fixed or dynamic — in either case, Adobe Coworker reasons and adapts until the desired outcome is reached.
6. Team collaboration. Your team and Adobe Coworker operate as “co-workers” in a shared workspace. Approvals and handoffs happen in one conversational environment — accessible from Adobe’s UI or Microsoft 365 Copilot, Claude, and ChatGPT.
Together, these six capabilities are what make agentic AI practical at enterprise scale – and the results from early customer programs show what that looks like in practice.
Where the architecture meets real work.
Across initial customer programs spanning industries, early deployments are already showing measurable impact. Some customers were able to drive 70% faster offer design and approval cycles, 60% fewer data onboarding delays, and launch campaigns 60% faster.
These results came from identifying three key areas that drain marketing teams' time and deploying Adobe Coworker to handle the operational work, so teams can stay focused on what requires their judgment and expertise the most.
Chasing operational exceptions. Every marketing operation runs into exceptions, but today those exceptions land in someone's inbox to pick up and manage on top of their other tasks. Adobe Coworker handles them directly instead — pausing dependent activities while it attempts remediation, then resuming execution once the issue is resolved. Your team sees only what genuinely needs a human decision while work keeps moving forward.
Maintaining always-on programs. Loyalty programs, price drop alerts, and lifecycle journeys are the campaigns that run continuously — and quietly consume enormous amounts of team time to maintain. Every week, someone is manually refreshing audiences, updating content, and adjusting rules to keep them current. Adobe Coworker absorbs that ongoing maintenance automatically, so your team can focus on the strategy behind these programs rather than the upkeep that keeps pulling them away from it.
Coordinating campaign launches. Getting a campaign from brief to live has always been as much a coordination problem as a creative one. Handoffs stall while people wait on each other, context gets lost between teams, and work sits idle until the next stakeholder has bandwidth. Adobe Coworker keeps the process moving by automating those handoffs and surfacing the right context at each stage — compressing a timeline that typically spans weeks into something that moves at the speed the market actually requires.
Every time Adobe Coworker completes a task, it adds to what it knows. That compounding knowledge makes the next exception easier to resolve and the next campaign faster to launch so that the impact goes beyond any single workflow.
The coordination ceiling has lifted.
Marketing has always moved at the speed of human coordination. Briefings, approvals, handoffs, and follow-ups have been the machinery behind every campaign – and it’s all been built around what people can manage manually.
That ceiling is lifting. Adobe CX Enterprise Coworker gives enterprise marketing teams the ability to operate with greater speed and clarity that simply wasn't possible before. It does this not by replacing the people behind the work, but by removing everything that was getting in their way.
Adobe CX Enterprise Coworker is available today. Talk to our team to learn more.
