First of all, not all AI tools are built for the same job.

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Copilot and ChatGPT are general assistants, powerful for writing, summarizing, and (with some work from you) automating tasks. But the quality depends entirely on the user’s own ability to structure, interpret, and judge what’s right.

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Tilda is a specialist and collaborative workspace built specifically for designing and measuring change. Just as you use a CRM for sales or an ERP for finance, you’ll need a dedicated system for change: in this case powered by AI (as most tools will be in the future).

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Tilda’s interface and architecture are structured for this exact workflow, streamlining it end to end.

It guides users step-by-step, keeps the red thread, ensures quality based on science, and produces outputs that are consistent and evidence-based. 

Here, the quality relies on Tilda’s built-in structure and peer-reviewed research, not solely on user skill.

It is designed to help organizations standardize, quality-assure, democratize, and continuously improve how change work is done, while building the organization’s structural capital over time.

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The results are tangible

Users report 69% less time spent and measurements show 84% improvement in quality of their change designs.

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“Tilda has genuinely streamlined my work and made the whole process more efficient. Tilda’s structure guided me all the way from goals to detailed design. It lets me go deeper than I normally can. And the Subject Matter Expert signed off my work with only minor edits”

Learning Product Owner, 500 fortune Company

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The next sections explain what makes Tilda fundamentally different from general AI tools — and why that difference matters for your organization.

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Tilda Quantifies Behavior Change

This is the core difference. Where general AI tools can explain behavioral science, Tilda can actually quantify it through our AI algorithm developed with research institute RISE and grounded in curated science. That means Tilda doesn’t just describe what might work (like Copilot/ChatGPT will), it can measure how effective your design is likely to be, and specifically where to improve it. 

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Tilda holds and structures your context

Tilda actually remembers every single detail of your change project. From goals, to audience and structure. This makes the work and output far more consistent and relevant. Whereas generalist AI tools have limited memory across chats and across time. You have to do a lot of prompting, reminding, fine tuning and uploading to get them to focus down on your specific needs.

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Tilda is a purpose-built workflow

Unlike a generalist AI chat tool, Tilda mirrors the actual workflow of learning design and change professionals. It can guide you step-by-step instead of just responding to ad hoc prompts and telling you what you want to hear. This saves time and reduces the back-and-forth that happens in just getting Copilot/ChatGPT to understand what you're trying to do.

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Tilda brings both quality and speed

Tilda helps users go deeper into detailed design and implementation much faster. Experienced users of Tilda can move from concept to production-ready material with SME sign-off in one flow. That level of quality and efficiency isn’t possible in a generalist AI tool, unless you have made the investment to build up your own custom workflow or agent.

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Tilda is scalable and inclusive

Another goal of Tilda is to make it possible for non-experts to create solid learning and drive change. This is where the guidance really comes into its own and Tilda can nudge, suggest and support, all grounded in behavioral science. Whereas with Copilot/ChatGPT you still need to have strong change skills to get good results.

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Tilda will get better and better

Tilda is, and always will be, laser focused on change programs and professionals. Generalist tools have to be all things to all people. They are swiss army knives. But sometimes you need a scalpel. We work every day to understand our users and how they work, to build features and bring updates that put you in the driving seat.

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Tilda vs Copilot/ChatGPT side-by-side comparison

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