AI in marketing at Futurice

The impact is clear. We produce work faster, but more importantly, with higher and more consistent quality. Our marketing team spends less time on repetitive tasks and more time on thinking, shaping narratives, and creating measurable impact for our clients.

From AI experiments to scalable marketing operations

Our AI journey in marketing began in 2023 with curiosity and small-scale trials. Today, AI is part of how work gets done. Every marketer has access to AI tools, supported by hands-on training and shared ways of working. We have built custom GPTs that reflect our real needs, including tone of voice, structure, and positioning, and are now moving these into Gemini Gems to enable broader use.

The most important shift has not been about replacing people. It has been about redesigning marketing processes. When AI handles repetitive steps, our experts can focus on insight, judgment, creativity, and quality.

Where AI delivers value in everyday marketing work

AI is embedded in our daily marketing activities, supported by automation and clear use cases. The most immediate value has appeared in digital marketing, content production, and event support.

In digital marketing, variation is constant. A single campaign often requires multiple versions of copy across formats and audiences. Our custom GPTs generate strong first drafts for ads and social posts, reducing turnaround times and improving consistency while keeping final decisions human-led.

In content production, subject matter experts continue to write thought leadership themselves. That perspective cannot be automated. For structured formats such as case studies and templated content, we use custom GPTs that understand our structure and tone. This ensures coherence and frees up expert time for higher-value work. For example, with our podcast production we were able to reduce production time by 50% with our CustomGPT and concentrate more time on the content itself, where us humans were still strongly in the loop.

AI also supports event-related tasks. An internal GPT, used when organizing smaller client events, helps with invitations, calendar entries, and agenda planning. Because shared templates are built into the tool, events across the organization meet a consistent professional standard.

Improving marketing quality without slowing teams down

One of the most important outcomes of adopting AI in marketing has been a change in how time is spent. Reducing the cognitive load of routine tasks creates space for quality. Reviews are sharper, narratives are clearer, and content is easier to adapt across channels and markets.

At the same time, speed has improved. Content created once can be reshaped into articles, social posts, campaign copy, or event materials without starting from zero each time. Faster does not mean lower quality. In practice, it often enables better quality by giving people time to think.

What CMOs should know about AI-driven marketing transformation

For CMOs, AI-driven marketing transformation is less about choosing tools and more about leadership. The real question is not whether AI can improve marketing performance. It can. The question is whether the organization is ready to change how marketing actually works.

A common mistake is treating AI as an efficiency layer added on top of existing marketing workflows. That approach can deliver short-term gains, but it quickly reaches its limits. If processes are still designed for an earlier digital era, AI mostly helps teams do the wrong things faster.

Based on our experience with enterprise marketing organizations, the familiar 20/80 view of AI transformation needs updating:

• Around 20 percent is technology. Tools matter, but they are rarely the main constraint.
• About 50 percent is process redesign and ways of working, including how campaigns, content, approvals, and handovers actually flow through marketing.
• The remaining 30 percent is cultural adoption, creating space for experimentation, learning, and continuous improvement.

CMOs play a central role in all three areas. You shape the conditions for experimentation, decide which processes are open for redesign, and signal whether AI is a strategic marketing capability or just another productivity shortcut.

How to start using AI in marketing teams

If you are at the beginning of your AI journey in marketing, start practical and grounded in real work.

Begin by mapping your current marketing processes. Without understanding how work flows today, it is difficult to apply AI meaningfully. Look for bottlenecks, repetition, and areas where quality suffers due to time pressure.

Next, focus on quick wins. High-impact and low-effort use cases, such as content variations, summaries, and structured formats, help teams see value early and build momentum.

Be deliberate about tool choices. Not every AI solution needs to scale across the entire organization immediately. For shared tools, a lightweight MVP often works better than aiming for perfection from the start. Custom solutions evolve over time; coaching and iteration are part of the process, not signs of failure.

Finally, invest in capability development. Teaching teams how to build, adapt, and critically evaluate AI outputs creates far more long-term value than rolling out a single tool. When people understand both the possibilities and limitations of AI, adoption becomes sustainable.

From AI experimentation to measurable marketing impact

For CMOs, the real measure of AI success is not how advanced the tools look, but whether AI supports the marketing work that drives business outcomes. When AI is embedded into everyday activities such as campaigns, content, events, and go-to-market execution, it becomes a capability rather than an experiment.

Organizations that succeed connect strategic intent with concrete use cases, redesign how marketing work flows, and actively support the cultural shift required for continuous improvement.

AI is not a destination or a one-off transformation initiative. It is an ongoing change in how marketing teams operate, make decisions, and create value. The opportunity is clear: use AI not just to do marketing faster, but to do it better, with more focus, more consistency, and more space for quality thinking.