What is AI Data Press?

AI Data Press is a trade publication covering data governance and the infrastructure behind production AI for data leaders, database and platform engineers, and the architects accountable for AI systems running in production . We report on the ideas, people and developments shaping data governance, database sovereignty, and the infrastructure behind production AI , with a particular focus on perspectives from the executives, operators and subject matter experts doing the work firsthand. Our readership is global and syndicated, and includes professionals at Fortune 500 companies and leading organizations across data management and AI infrastructure . Our goal is to give practitioners a useful place to learn from their peers and give experts a credible platform to contribute their experience to important industry conversations.

Someone reached out to interview me. Why was I invited?

We believe in humans! The only thing AI-generated content will never replicate is the unique perspectives we all have as professionals. We regularly speak with senior executives, operators, practitioners, researchers and other subject matter experts whose experience is relevant to the topics we cover. Our editorial team is always on the lookout for potential contributors based on their professional expertise, experience and perspective. Interviews are designed to surface useful firsthand perspectives rather than promote a product or company. For participants, they provide an opportunity to contribute to the conversation around their field, share lessons from their work, and build a published body of thought leadership around the subjects they know best. Also, we hate that we even have to say this, but there is no fee to participate . There are many known scammy news sites out there that make thought leaders pay for coverage in small trade publications. We do not do that.

What are some examples of interviews you've done?

A sense of the work, and of who talks to us: Director of Engineering and Program Management at Cisco — Engineering Moves From SDLC to ADLC as Agents Shift Upstream Into Planning Principal Technical Product Manager at Mayo Clinic — Mayo Clinic Builds Trust in Healthcare with AI-Optimized Patient Experiences Senior Manager, Marketing at Qualcomm Technologies — From Cloud to Device, AI Business Models Are Coming Down to Earth

What does "Powered by EnterpriseDB" mean?

AI Data Press is sponsored by EnterpriseDB , whose support makes it possible for us to produce ongoing reporting, interviews and industry coverage around data governance and the infrastructure behind production AI . Rather than relying primarily on traditional display advertising or a reader paywall, the publication is supported by a single company with a strong connection to the industry we cover. We disclose that relationship so readers and contributors can clearly understand how the publication is supported. The articles and interviews themselves are produced by the AI Data Press editorial team . Experts are invited because their perspectives are relevant to our coverage, not because they have paid to appear, and participation does not require a commercial relationship with or endorsement. An interview invitation from AI Data Press should therefore be understood as an invitation to contribute expertise to an editorial trade publication, not as a sales solicitation or paid placement.

I need company approval to speak publicly. Can you work with our Comms or PR team?

Yes, and we do it often. Many of the people we interview work at large organizations where speaking to a publication involves communications, PR, legal or executive review. That is normal, we expect it, and it is never a reason not to talk to us. Here is what we can offer: We will work directly with your communications or PR team. Put us in touch and we will answer their questions, explain the format, and follow whatever process they need. If it is easier for them to sit in on the conversation, that is fine. We can provide the article for review before publication, on request. If your organization requires sign-off, tell us early and we will build that step into the schedule so it does not become a scramble. We can add a personal opinion disclaimer. Where you are speaking for yourself rather than your employer, we will state that plainly in the article, for example: "The opinions expressed in this article are those of [contributor name] alone and do not necessarily reflect those of any organization." You can decline any question, or ask us to keep something off the record. Tell us during the conversation and it does not appear. If you would like your communications team to reach us first, or you want to check with them before responding, email us at editors[at]aidatapress.com and we will take it from there. There is no deadline pressure attached to that conversation.

Where will my interview appear, and who will see it?

Your interview will be published on AI Data Press ( https://www.aidatapress.com ), where it becomes part of our ongoing coverage of data governance and the infrastructure behind production AI and can continue to be discovered and referenced after publication. Our audience includes data leaders, database and platform engineers, and the architects accountable for AI systems running in production at organizations around the world, including professionals at Fortune 500 companies and other leading enterprises. We also make interviews easy to extend through professional networks and LinkedIn distribution. Contributors receive a shareable article link and professionally designed quote-card asset that can be used on LinkedIn, and stories may receive additional amplification through the publication, contributor networks and relevant professional communities. For many contributors, the value is not simply appearing in one article. It is having their expertise captured in a credible editorial format that can be shared with colleagues, customers, peers and their broader professional network.

How Data Leaders and Infrastructure Architects Get Interviewed and Quoted as Expert Sources

Getting quoted or interviewed as a data infrastructure expert almost always comes down to the same thing: a specific, firsthand claim, offered to the right outlet, at the right time. Titles and years of experience help you get a reply, but a concrete point of view is what gets you booked.

What Editors are Actually Looking For

Editors covering data governance and AI infrastructure aren't looking for someone willing to comment generally on AI or data. They want the person who actually ran the migration, owns the governance policy, or made the call on where a workload runs, and can describe what happened in specific, attributable terms.

The main avenues

Responding to journalist queries. Services like Connectively (formerly HARO), Qwoted, and SourceBottle send daily requests from reporters looking for sources, including data and infrastructure queries.
A strong, specific LinkedIn presence. Editors search LinkedIn for people already talking publicly about data governance and infrastructure decisions, not just company news.
Pitching trade publications directly. Most trade outlets, AI Data Press included, accept unsolicited pitches from people not already on an editor's radar.
Industry podcasts. Podcast hosts are often easier to reach than journalists and are always looking for a guest with a specific story.
Speaking and panels. Conference talks and webinars are a common way editors first notice a potential source.

How to Pitch Yourself to a Trade Publication

Who you are: role, company, and why it's relevant.
The one specific thing you can speak to: a decision you made, a result you can quantify, a contrarian view grounded in your own work (e.g. why you moved a database off a managed service, or what broke during a migration).
Why now: a news hook, an early trend, or a lesson from something that just happened.

Keep it to a few sentences. A pitch that reads like a press release about your company, rather than a claim only you can make, gets skipped fastest.

Contributing to AI Data Press

AI Data Press covers data governance and the infrastructure behind production AI, and regularly interviews data leaders, database and platform engineers, and the architects accountable for AI systems running in production. Participation is free. There is no placement fee.

Pitch yourself at https://www.aidatapress.com/pitch-us.