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8 Takeaways from Scott Brinker's Martech for 2026 Report (That Apply Way Beyond Marketing)

  • Writer: Tara Cruz
    Tara Cruz
  • Jan 12
  • 2 min read

Scott Brinker's Martech for 2026 report came out yesterday. While the data is marketing-specific, the patterns it highlights are showing up across the board, from HR and IT to RevOps and transformation teams.


In short: AI capability is moving faster than most organizations can absorb.


AI Capabilities

Here are the key takeaways I think matter across functions, not just for marketers.


1. Technology Is Ahead of People and Process


Technology readiness is higher than human or organizational readiness.

The biggest opportunities right now aren’t about adding new tools—they’re about:


  • Upskilling teams

  • Clarifying ownership and decision rights

  • Investing in structured change management


Until those gaps are addressed, AI will continue to underdeliver relative to its potential.


2. Everyone Is Still Early, and That’s Normal


Despite all the noise, only 23.3% of respondents have AI agents deployed in full production use cases.


That means the majority are still:

  • Piloting

  • Experimenting

  • Running proofs of concept


3. The Most Common Agent Use Cases (So Far)


The agent use cases that are sticking so far tend to be high-leverage and repeatable:


  • Content production

  • Customer service chatbots

  • Audience discovery and segmentation

  • Competitive analysis


4. Top Implementation Challenges


Two issues are holding teams back from scaling:


Data quality:


  • Missing or outdated records

  • Inconsistent formatting


Organizational readiness:


  • Skills gaps

  • Unclear ownership

  • Resistance to change


These aren’t AI-specific problems. They’re long-standing issues AI now makes impossible to ignore.


5. How Teams Are Actually Building Agents


Most companies aren’t starting from scratch.

According to the report:


  • 62.1% are using agents embedded directly in existing martech platforms

  • 49.5% are using iPaaS and low-code tools like Gumloop, Make, n8n, Workato, and Zapier


6. Top Internal Data Sources for Agents


The most common internal data powering AI agents:


  • CRM and CDP profiles

  • Brand and marketing assets

  • Email communications

  • Brand voice and style guides

  • Knowledge bases


In short: agents are only as effective as the institutional knowledge they can access.


7. Top External Data Sources


Internal data isn’t enough. The top external data sources include:


  • Customer and prospect profile enrichment data

  • Public web content, especially prospect websites


Combining internal context with external signals is where real value emerges.


8. Most “Agents” Are Still Just Assistants


Perhaps the most grounding stat in the report:


81% of what people call agents are actually assistants.


That means:


  • AI suggests

  • Humans decide


Fully autonomous agents are the exception, not the norm and for most teams, that’s exactly where things should be.


Bottom line: AI capability is here. Organizational capability is catching up.

The teams making progress aren’t ahead because they bought more tools. They’re ahead because they made time to train people, fix broken processes, and get real about where AI fits.


Source: Scott Brinker, Martech for 2026 Report link:https://content.martechday.com/martech-for-2026.pdf



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