Artificial Intelligence is no longer that exciting novelty everyone tested but few actually knew how to use for real.
Marketing teams are living this firsthand: the experimentation phase is behind them, and now the conversation has shifted entirely.
Agentic AI stepped onto the scene not as just another tool in the arsenal, but as a kind of work partner — someone who helps think, draft, research, and keep the workflow moving.
And there is one stat that sums up this moment perfectly: 73% of professionals using agentic AI say it has increased their confidence in their own performance.
That is no small thing.
It means automation is not just speeding up deliverables — it is changing how people feel about their own work.
To better understand this shift, Adobe surveyed more than 1,000 full-time American workers who use AI weekly, and what emerged from that research goes well beyond the numbers.
It is a snapshot of how work is being reinvented, especially for those embedded in creative and communications teams. 🎯
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What Adobe’s research revealed about AI and professional confidence
The research was built on a simple premise: understanding how American professionals are actually using Artificial Intelligence day to day — not just what they think about the technology in theory. The sample was sharp — full-time workers who have already woven AI into their weekly routine — which makes the data far more real and actionable than a generic perception survey. The most striking result was exactly that 73% figure, showing that using agentic AI is not just a productivity play but also a matter of self-confidence and how each professional sees their own value within the team.
One data point that really stands out is how people choose where to seek help. When asked who they would turn to with an obvious question, 68% chose an AI agent, compared to just 4% who would go to their direct manager. That means workers are 17 times more likely to ask an AI something they would hesitate to bring to leadership. It is a clear portrait of how technology is lowering that barrier of fear — the fear of looking unprepared — by offering a judgment-free space to figure things out.
When we talk about confidence in the context of creative work, we are talking about something very specific: the feeling that you can deliver on what you promise, that your ideas have stronger backing, that your process has less noise and more results. And that is exactly what agentic AI seems to be providing for a significant portion of these professionals. It acts as a support layer that validates, complements, and accelerates decisions without taking the spotlight away from the person in charge. This is different from a tool that simply automates mechanical tasks — here we are talking about a more sophisticated collaboration.
Another interesting point surfaces when we look at remote workers. They are 35% more likely than their in-office counterparts to report reduced impostor syndrome and mental load thanks to agentic AI. It makes total sense: people working from home do not always have someone nearby to answer a quick question, and AI ends up filling that gap, offering real-time support and helping keep things moving without the anxiety of being alone in the process.
Automation that respects the creative process
One of the biggest concerns that comes up when automation enters creative teams is the fear that technology will flatten the process, turning something that should be unique into something generic. But what Adobe’s research points to moves in the opposite direction. When properly integrated into the workflow, AI does not replace human judgment — it amplifies the capacity of the person creating. The difference lies in how that integration happens: not as a shortcut to skip steps, but as a resource that makes each step richer and less draining.
For marketing teams, this translates into very concrete gains. Imagine a team that needs to produce content for multiple channels simultaneously, with tight deadlines and very distinct personas. Before, that scenario required either a bigger team or lower quality in the output. With Artificial Intelligence acting as a partner in the process, it is possible to maintain quality, adapt tone for each channel, and still have time left for more careful revisions. This is not magic — it is automation applied intelligently, respecting what human creativity does best: making choices with meaning.
Where AI enters the daily workflow first
The research shows that AI agents are especially useful in the early stages of work. By taking on tasks like research, idea generation, and first drafts, they free up professionals to focus on strategy and creative direction. Among the most common uses are idea generation and brainstorming at 52% adoption, content creation and writing at 50%, and research at 31%. These are precisely the beginning-of-process activities that deliver immediate value, helping teams move faster without sacrificing quality.
The work environment also shapes how AI is used. Remote workers, for example, lean on AI more heavily for quick clarifications, replacing those informal hallway conversations so common in offices. The data shows that in-office professionals are 14% less likely than remote workers to ask basic questions to AI, while hybrid workers are 53% more inclined to use the technology to optimize workflow compared to in-office teams.
There is also a positive side effect that often goes unnoticed: the reduction of creative stress. When a professional knows they have an intelligent support layer to help structure ideas, research references, or even review a piece before delivery, the pressure drops. And with less pressure, creativity tends to flow better. This virtuous cycle is one of the factors explaining why so many professionals report increased confidence when using agentic AI. The machine is not doing the work for them — it is making their work more sustainable. 🚀
AI as a coworker who does not judge
One of the most fascinating shifts brought by agentic AI is how people choose where to ask for help. In many everyday situations, workers feel more comfortable asking an AI agent than asking a manager or even a colleague. Whether it is a simple question or a first draft, AI offers a fast, low-pressure way to get unstuck.
This dynamic becomes evident in moments where hesitation is common. For drafting a difficult or high-stakes response, 54% prefer AI, compared to 23% who would turn to either managers or colleagues. For taking the first step on a complex project summary, 62% choose AI, versus 10% who would go to their manager. The same pattern shows up when recapping an important meeting or recalling forgotten software workflows.
But there are limits, and that is healthy. When the stakes get higher, people still prefer to rely on each other. A clear example: 43% of workers prefer to validate a risky idea with a colleague, compared to 39% who would turn to AI. This preference for human collaboration is even stronger among younger workers. Gen Z, for instance, tends to consult colleagues for complex or sensitive tasks, revealing an attachment to social trust that is typical of people early in their careers.
How marketing teams are reorganizing work with AI
Integrating Artificial Intelligence into the workflow of creative teams does not happen in a straight line. Each team finds its own entry points, and Adobe’s research shows that the professionals most satisfied with the technology are those who incorporated it organically — without forcing adoption that does not make sense for their context. In marketing teams, the most common use cases involve generating initial drafts, analyzing campaign performance, personalizing messages at scale, and organizing briefs and editorial calendars. These are functions that consume a lot of time and energy when done manually but gain speed and precision with AI support.
Leadership’s role in this process is also decisive. Teams with managers willing to experiment alongside the team — rather than just demand results — tend to advance faster on the adoption curve. When confidence comes from the top, it spreads through the team naturally. And when the team feels it can make mistakes, adjust, and learn without judgment, the relationship with automation stops being threatening and becomes collaborative. This is a point Adobe’s research reinforces consistently: technology alone does not transform work — the cultural context it is embedded in is what defines the real impact.
Gains that vary by industry and profile
The impact of AI on confidence is even stronger in complex, high-stakes sectors where precision and speed make all the difference. In finance and banking, 87% report improved performance. In technology, that number reaches 80%, followed by retail and e-commerce at 78%, healthcare at 66%, and education at 65%. In these environments, the ability to verify information quickly and reduce uncertainty carries enormous weight in both outcomes and the peace of mind of those doing the work.
The benefits also go beyond pure efficiency. Half of professionals report having freed up time for higher-value tasks, 38% point to productivity gains, and 36% say they experienced reduced impostor syndrome. That last data point is especially revealing: AI is helping people validate their reasoning in real time, reducing that nagging need to second-guess their own decisions. It is worth noting, however, that early-career professionals are the least likely to report increased confidence, which highlights a clear opportunity to improve support for those just starting out.
- Generating drafts and initial content with more speed and less creative block
- Analyzing campaign data with faster and more actionable insights
- Personalizing messages at scale without losing brand identity
- Organizing briefs and editorial calendars with more clarity and less rework
- Reviewing and optimizing copy before final delivery to clients or the public
The gap between training and practice still exists
Despite all this enthusiasm, the research reveals an interesting disconnect. Although one in three professionals has received formal training in agentic AI, less than half of them — just 46% — have actually built their own custom agent. This shows that learning the theory is one thing, but turning that knowledge into practical application is something else entirely.
The curious part is that formal training is rarely the starting point for AI fluency. For most people, learning to use these tools is a self-taught process driven by curiosity, collaboration with peers, and a willingness to experiment. Among the most common learning methods are trial and error at 54%, YouTube at 36%, collaborative learning with colleagues at 25%, and Reddit at 23%.
Some sectors are further along in this journey, especially those with more regulated environments. Finance and banking lead the way, with 51% of professionals having received training in agentic AI, followed by technology at 48%, healthcare at 31%, retail and e-commerce at 29%, and education at 27%. Even with this learning curve, seven out of ten workers already see AI as a way to rethink how they work — not just as a tool to go faster.
Building the marketing team ready for the AI era
Another aspect worth highlighting is the shift in the skill profiles that are becoming more valued within these teams. With AI taking on more operational tasks, marketing professionals are increasingly recognized for their ability to think in systems, understand human behavior, and translate data into narratives that connect. These are skills that have always been important but often took a back seat to the urgency of deliverables. With automation shouldering part of the operational load, these competencies gain space and visibility — and people start feeling more complete in what they do. It is this combination of technology and humanity that is redesigning what it means to do good work.
Agentic AI is establishing itself as an indispensable resource for many teams. It helps fill knowledge gaps, keeps people in the loop on their own work, and builds more security in what they are delivering. This impact is even more evident for remote and distributed teams, as well as those operating in complex or highly regulated environments. There is still a distance between what AI can do and how teams actually use it, and training alone does not close that gap. The technology needs to be integrated into real work — not isolated in standalone features.
At the end of the day, what Adobe’s research makes clear is that Artificial Intelligence is fulfilling a role that goes well beyond operational efficiency. It is helping professionals reconnect with what they enjoy most about their work — the creative, strategic, and human side of the process. And when that happens, confidence is not just a number in a survey: it shows up in the results, in the deliverables, and in how each person presents themselves within their own team. The real opportunity lies in making AI a natural part of how work happens — and the teams that master this will move faster, stay more organized, and deliver more personalized experiences at scale. ✨
