If AI were a person, it would be walking around with a target on its back.
The technology gets blamed when reports show organic referral traffic declining and consumers turning to answer engines rather than visiting websites directly.
It’s just as tempting to point the finger at AI when employees struggle to adopt new tools that require developer-level expertise.
Then there are the security concerns that suggest AI is too inherently risky to deploy further across the enterprise.
AI isn’t really at fault in these scenarios, but it may be exposing the fault lines that lead to common business challenges.
Your efforts to champion AI internally will go further if you:
1. Reframe the AI ‘gatekeeper’ perception
A lot of enterprise marketing content has been buried or deliberately put behind forms that require your customers and prospects to take extra steps to get answers.
AI summaries and overviews simply offer the short-cut many buyers have wanted all along.
Fortunately, there are architectural decisions you can make today that can optimize your site for people and AI answer engines at the same time.
2. Keep two types of AI users top of mind
Developers have plenty of tools and APIs available to help them understand AI’s capabilities and turn them into real-life projects.
Those on the front lines, like content teams, require just as much consideration as deployments are planned and executed.
This is an opportune moment to ask if the AI-powered tech stack you’re building is addressing everyone’s needs.
3. Become fluent in CSO-speak
The use cases you used to get the green light for AI investments hit differently when you’re in charge of safeguarding an organization’s data.
CSOs get unfairly labelled as the ‘No’ people because they can’t afford to have technologies like AI violate policies or attract cybercriminals.
Use this guide to get on the same page with your CSO about AI and other emerging innovations.