Liza Adams

A year ago, I started “Practical AI in Go-to-Market” with one simple belief. We’re all learning together in this AI world, so why not share the journey?

Today, I’m looking back on something I never expected. Over 8,000 GTM leaders, from account execs and product strategists to CMOs and founders, now get this newsletter every two weeks. More than the number, the community we’ve built matters most.

• ➡︎ To the readers who forward these emails to teammates, you’ve made the impact bigger than I ever imagined.

• ➡︎ To the leaders who’ve tried these ideas with your teams, seeing your wins reminds me why I started this work.

• ➡︎ To the people who’ve shared your AI experiments with me, your willingness to try, fail, and share keeps pushing all of us forward.

• ➡︎ To everyone who’s challenged my thinking, you’ve made every newsletter better and more inclusive.

This milestone means so much more to me. There’s room for natural sharers in business. For those of us who believe when one person succeeds, we all can. For those who see business as a way to do good.

For years in corporate jobs, I wondered if sharing openly was holding me back. In the right place, it became my biggest strength.

The AI world created that place. When nobody has all the answers, the people willing to learn out loud become the most valuable, not the most vulnerable. When everything changes this fast, sharing what you know generously becomes necessary for everyone’s success.

To anyone building something you’re passionate about, your real voice counts. Your willingness to help others win is what sets you apart. The right people will find you when you build something valuable and share it openly.

Thank you for being part of this journey. Whether you’ve been reading from day one, just subscribed, or you’ve never opened one of my emails but read this far, you’re proof that learning together works.

See original post here

Many are sharing charts about Reddit and Wikipedia dominating AI search mentions, desperately trying to crack the code. The answer is in plain sight, but they’re too busy looking for shortcuts.

These platforms get sourced because they directly answer real questions using language real people actually use.

I’ve been watching GTM leaders react to this data. They nod along when I explain the approach, then immediately ask for the algorithm hack. They want the Ozempic for AI search that bypasses the actual work of understanding customers.

I’m noticing that teams fall into two buckets:

• ➡︎ Teams that do the work – They audit their content, analyze customer language, map out funnel questions, and create genuinely helpful answers. Yes, it’s hard and takes time. But they’re treating the cancer, not putting a bandaid on it.

• ➡︎ Teams chasing shortcuts – They say “that will take too long” and keep searching for the algorithm. They want to look trustworthy without being trustworthy.

Reddit works because real people solve real problems in real language. Wikipedia gets cited because decades of helpful content builds trust. But note that Business/Service sites are getting 50% of citations, showing the opportunity exists.

Many companies don’t understand their customers well enough, especially given that markets have shifted and behaviors have changed. They haven’t:

• ➡︎ Figured out what customer AI inquiries look like at each funnel stage

• ➡︎ Created content that directly answers those questions using customer language

• ➡︎ Been honest about when they’re the best fit and when they’re not

• ➡︎ Put content and engaged authentically in trusted watering holes (e.g., communities, publications, review sites, social channels) where customers hang out

AI is looking for signal, not noise. When your content shows up consistently across channels answering real questions, that becomes signal.

AI amplifies what’s already there – whether what’s there is good or bad. Be genuinely helpful and let the cards fall as they may.

Chasing algorithms is futile. The AI companies probably don’t even know their own algorithms, and it changes constantly.

This is about building trust. What would it take for someone to earn your trust? Mowing your yard versus finding daycare for your children. The bigger and the more important the pain, the more intense the trust-building needs to be.

High-intent buyers choose companies they trust to solve real problems, not AI search hacks.

Stop chasing algorithms and start earning trust. Be genuinely helpful to real people with real problems. I shared links to a couple of newsletters in the comments below that show you how. Something for your consideration for those of you who like to do some weekend learning.

AI Search Related Newsletters:

1. 1) Make Your Brand Relevant in AI Search – https://www.linkedin.com/pulse/make-your-brand-sourced-top-result-ai-search-practical-liza-adams-qmarc

2. 2) When AI Judge Your Brand Before Humans Do – https://www.linkedin.com/pulse/when-ai-judges-your-brand-before-humans-do-liza-adams-8xuyc

3. 3) Creating Standout Content When 50% of Web Traffic Disappears – https://www.linkedin.com/pulse/beyond-ai-generated-content-guide-standing-out-when-50-liza-adams-asnpc.

See original post herehttps://www.linkedin.com/posts/lizaadams_many-are-sharing-charts-about-reddit-and-activity-7364645522525126656-NbEL?utm_source=share&utm_medium=member_desktop&rcm=ACoAAEFyZhcBeBOPDDQ2WZbpFE9UiuhHuj5zo-Q

Many teams use AI like a Magic 8-Ball. They ask a question, get an answer, and move on to the next task.

The teams making real impact go beyond using it to do a task quickly. They’re using AI to make better decisions and find approaches they’d never think of alone. As they say…

we can’t reimagine the future by simply automating the past.

While everyone else stops at productivity gains, some leaders are going further, using AI to pinpoint blind spots and challenge their assumptions. Most just haven’t seen how.

This week, I saw this change happen IRL with 60+ marketers at Cox Automotive Inc., the company behind Kelley Blue Book and Autotrader that helps dealers and partners buy and sell millions of vehicles each year.

When teams stopped asking AI to do tasks and started asking it to poke holes in their plans, the team dynamics changed. Conversations went deeper and were more insightful. People started spotting problems they’d missed.

Here are some key learnings:

• ➡︎ Teams using AI just for speed miss the real opportunity to make better decisions and come up with fresh ideas

• ➡︎ The probing questions that make your AI conversations better show up in every meeting and planning session

• ➡︎ This approach works on everything from email subject lines to campaign plans and expansion strategies

Because we’ve long been rewarded for good answers, many may not be as adept at asking thoughtful questions. Every AI conversation becomes critical thinking practice. Pushing AI then becomes automatic and a habit.

I break down the complete three-level critical thinking framework with sample questions and a starter kit to help you apply this to your specific projects. Full details in the newsletter below.

Prefer audio? There’s a 13-minute AI podcast version in the comments, perfect for your commute or while multitasking.

Huge thanks to Mandy Dhaliwal (CMO of Nutanix), Ramon L. Cortes (AVP of Cox Automotive), and Sydney Sloan (CMO of G2) for sharing insights on how they use AI as a thought partner for both tactical and strategic work.

How much do you use AI to speed up work? Make better decisions? Find new ways?

Here’s the 13-min AI podcast version of this newsletter to support different learning styles. Listen while driving, walking the dog, or having lunch 😉

https://drive.google.com/file/d/1KZzMxGeR-dSiTgugukPVqxJigyRKaaDv/view?usp=share_link

Give it a few seconds to load after you hit play.

Note: AI-generated using Google’s NotebookLM and reviewed by me for accuracy and responsible AI use. See original post here