AI is everywhere – but that doesn't mean it belongs everywhere. In this first webinar of our 'Just add AI' series, we show you how to cut through the hype and panic to implement AI thoughtfully.
Video: AI's Digital Experience Impact. Captions and transcript available on playback.
How AI is reshaping digital experiences, common implementation pitfalls, and a practical framework to successfully adopt AI in websites and digital services.
Both easy to find and accurate - we’re in good shape – 6%
Easy to find but accuracy could be better – 16%
Accurate content but can be hard for users to find – 52%
Neither easy to find nor consistently accurate – 13%
Not sure - we haven’t measured this – 13%
Start with how an intern can help you. Your approach should be:
> Think of AI as a useful but untrustworthy intern
> Ask it to do tasks like creating 5 variations of text for different audiences (Gen Z, elderly, etc.)
> Review and select or tweak the results
> Use it for tasks like answering FAQ questions, but don't put it in charge of the call center
Key mindset: "How do I integrate this useful but untrustworthy intern into my workflow to help me get my job done faster?"
Here's a university case study example:
This was low-risk because it helped people who already knew the answers find information faster, rather than making AI the primary source of answers.
GEO stands for Generative Engine Optimization. It's about making sure your information appears in AI search solutions like ChatGPT, Google AI, etc.
Key principles (similar to SEO foundations):
The bottom line: Having really good content will help you - AI systems will naturally find it easier to work with clear, accessible content. This also helps regular visitors, not just AI systems.
Content audits usually reveal what you suspected already - that there are content issues all over the place. All organizations have issues to some degree, the trick is identifying the specific set of information that is in high demand / needed as input for AI, and the extent of specific issues within that.
It doesn't matter if a page that was last viewed by a visitor in 2017 has bad content. Once you identify the content you care about, you can scan for potential issues or try running our testing tool to see how AI would use it and triage the issues.
The challenges are the same as other tech implementations.
Common organizational hurdles you'll face:
Navigation strategies you should use:
The key is getting everyone in the room, talking to them, understanding all their concerns, understanding the business and then navigating how to address all those issues with appropriate solutions.
Yes, absolutely. This is critical.
The problem: There are thousands of vendors of AI chatbots out there, and it can be as easy as signing with one in the morning and deploying it on your website in the afternoon. The risk is that you could then see your name in the newspaper for all the wrong reasons by tomorrow lunchtime.
Your solution process should include:
Timeline: It's not a 24-hours-and-it's-live thing. It's a 3-month process to build confidence before public deployment.
The core issue: People have a cognitive bias thinking it's a computer system, that it's objective and unbiased and, therefore, just accept answers without thinking.
The reality: LLMs were trained on things found on the Internet... and then post-trained by specific groups of people. So instead of being an objective computer system, we just managed to codify all of humanity's biases into this black box that we can't see.
Practical approaches you can use:
