One question clients ask me regularly is whether they should stop paying for stock photography, skip professional photo shoots, and simply use AI-generated images instead.

My answer is usually the same:

Not so fast.

AI image generation is a remarkable tool. It can help businesses create content faster, reduce creative costs, and produce visuals that would have been difficult or expensive to create just a few years ago. But if you’re thinking AI images will completely replace authentic photography, I think that’s the wrong way to look at it.

The better question is: What type of image works best for the job?

After years of helping companies improve lead generation, conversions, and online visibility, I’ve come to a simple conclusion:

AI is a powerful marketing tool, but trust is still what converts potential customers into leads or sales.

The businesses getting the best results today are not choosing AI instead of photography. They’re strategically combining AI-generated imagery, authentic photography, and stock images based on the page’s purpose and the visitor’s expectations.

Google Doesn’t Care If an Image Was Created by AI

One of the biggest misconceptions I hear is that Google penalizes websites simply for using AI-generated images.

That’s not how Google evaluates content.

Google has repeatedly stated that it focuses on quality, usefulness, and the overall user experience, not the tool used to create the content. An AI-generated image is not automatically a ranking problem any more than a stock photo or a professionally taken photograph is automatically a ranking benefit.

However, that doesn’t mean all AI-generated imagery is created equal.

Problems can arise when businesses use AI images in ways that hurt user trust or create a poor experience. For example, an AI-generated image that implies a product, location, customer, or event is real when it isn’t can be misleading. Likewise, filling a website with generic AI artwork that adds little value to the page may reduce engagement and make the content feel less credible.

Another issue I frequently see is performance. Some AI-generated images are uploaded without optimization, resulting in unnecessarily large file sizes that slow page load times. Since site performance remains an important ranking factor, businesses should treat AI-generated images the same way they would any other visual asset—compress them, optimize them, and make sure they contribute positively to the user experience.

The best approach is to use AI imagery thoughtfully. Add descriptive alt text, provide context where appropriate, and reserve authentic photography for situations where users expect to see real people, products, facilities, or locations.

In other words, Google isn’t evaluating whether an image was created by AI. It’s evaluating whether the image helps users and supports a trustworthy experience.

Where AI Images Make a Lot of Sense

For content marketing, AI can be incredibly valuable.

If you’re publishing blog posts, educational resources, social media content, webinar promotions, email campaigns, or SEO-focused articles, AI-generated imagery can save significant time and money.

Instead of spending hours searching through stock libraries for an image that sort of fits your topic, AI allows you to create visuals specifically designed for the content you’re producing.

AI-generated images can also help businesses create more unique visual experiences. Traditional stock photos are often used by thousands of websites. Custom AI imagery can better support educational content, explain complex concepts, and provide visuals that are closely aligned with search intent.

For companies producing a high volume of content, that’s a meaningful advantage.

But Trust Still Matters

This is where I think many marketers get carried away.

Just because AI can create an image doesn’t mean it should.

If someone visits your website and is considering hiring your company, they want to know who they’re doing business with. They want to see real people, real expertise, and real evidence that your organization exists beyond a collection of marketing claims.

An AI-generated image of your leadership team is not a substitute for actual leadership photos.

An AI-generated office scene is not a substitute for showing your real company.

An AI-generated customer isn’t a substitute for a real client story.

When trust influences buying decisions—and it almost always does—authenticity matters.

Why Authentic Photography Still Wins in Important Places

Some of the highest-converting pages on a website are also the pages where trust matters most.

Think about your homepage, About Us page, leadership profiles, recruiting pages, customer success stories, and testimonials.

These are the places where visitors are evaluating credibility. They’re looking for signals that your company is established, experienced, and trustworthy.

Authentic photography does something AI can’t fully replicate.

It demonstrates that there are real people behind the business.

I’ve always believed that marketing works best when it reduces uncertainty. Real photography helps accomplish that. It reassures prospective customers that they’re dealing with a real company staffed by real professionals.

This is particularly important in industries such as healthcare, financial services, legal services, consulting, education, and other professional services, where expertise and trust heavily influence buying decisions.

Stock Photography Still Has a Place

Stock photography doesn’t get as much attention these days, but it still serves an important role.

A professionally produced stock image is often better than a poorly executed AI image. Stock libraries also provide commercial licensing protections and access to high-quality visuals that can be deployed quickly when custom photography isn’t practical.

The challenge is that stock photography can sometimes feel generic because so many businesses are pulling from the same libraries.

That’s why I generally view stock photography as a useful supporting tool rather than the foundation of a company’s visual identity.

The Reality Facing Marketing Teams Today

There’s another factor influencing this discussion.

Marketing teams are shrinking.

Many companies are asking smaller teams to create more content than ever before. At the same time, experienced marketing professionals are difficult to hire and expensive to replace.

That’s one reason AI imagery has become so attractive. It allows lean teams to create blog graphics, social media visuals, webinar promotions, and supporting content much faster than traditional creative workflows.

But speed alone isn’t the goal.

The goal is to create effective marketing that generates trust, engagement, and conversions.

That’s why I don’t see AI replacing professional photography. I see it helping marketing teams become more productive while allowing them to reserve their time and budgets for the places where authenticity has the greatest impact.

My Recommendation

If I were advising most businesses today, I would recommend a hybrid approach.

Use AI-generated imagery where scale, efficiency, and content production matter most. Blogs, educational resources, email campaigns, social content, and other content-heavy initiatives are often great candidates.

Use authentic photography where trust, credibility, and brand differentiation matter most. Your homepage, leadership pages, team pages, recruiting content, and customer stories should showcase the real people behind your business.

Use stock photography selectively when you need professional visuals quickly and custom photography isn’t practical.

In other words, don’t choose AI instead of photography.

Choose the right image for the right purpose.

Final Thoughts

AI is going to become a permanent part of modern marketing. There’s no question about that.

But the future isn’t “AI replaces photography.”

The future is businesses learning how to combine AI efficiency with authentic human trust.

The companies that do that well will create more content, build stronger brands, improve their visibility in search, and ultimately generate more conversions.

Technology can help tell your story.

It shouldn’t replace the people, experiences, and expertise that make your story worth telling in the first place.

About the author:

Andy Hoover helps Beasley Direct and Online Marketing, Inc., clients grow their online presence through Google Ads, SEO, and LinkedIn Advertising. He partners with clients to create data-driven strategies that increase visibility, drive quality traffic, and generate leads. He is passionate about staying ahead of digital trends, testing new tactics, and optimizing every aspect of a campaign to maximize success. Whether improving ad performance, increasing organic search rankings, or fine-tuning audience targeting, he thrives on helping businesses achieve their marketing goals.

The post AI Images, Stock Photography, or Real Photos? My Take After Years in Marketing. appeared first on Beasley Direct and Online Marketing.

What is Google up to? Looking at the various Google tools and features, here is what I see is happening at Google.

Google has been developing Google Data Studio (GDS) for several years (this is their free version comparable to Salesforce Tableaux). Both are data visualization tools, which means they pull in data from multiple sources, tools, and databases to create visually appealing reports. Google sees Google Data Studio as a reporting overlay for Google Ads, Google Analytics, Google Search Console, and other tools. All those tools will send data to Google Data Studio. We’ll explain later where we see Google headed with Google Data Studio as it continues to update other tools.

Google Analytics was updated to Google Analytics 4.0 (GA4) in October 2020 and now, a year later, many companies are using it.

Universal Analytics, the previous version, was only a reporting tool. It collected and displayed website data. But GA4 isn’t an update. It’s an entirely new concept of data on the web.

The most powerful feature in Google Analytics 4.0 is predictive analytics. It can predict data. How does it do that? Google bought DeepMind (an AI company) in 2014 for $600m. David Silver at DeepMind developed Reinforcement Learning (a new type of Machine Learning). He developed Alpha Go to play the game of Go (Wei chi). Chess is easy for machine learning: the rules let one predict future steps. Alpha Go however is vastly more complex. How much?

Alpha Go has 10¹⁷⁰ combinations (there are only 10⁸⁰ in the universe). Instead of rules and steps, Alpha Go looks at patterns. In 2016, it won against the world champion. A year later, Alpha Go Zero won 100 straight games against Alpha Go, the previous version.

It’s important to understand these game-playing AI are not controlled. Tens of thousands of games in chess and Go have been recorded over the last three hundred years and are well-known to grandmasters. But the AI often makes moves that have never been seen before. The AI discovers patterns and opportunities that humans have never played.

Google owns this AI software, so it has been applying it to their software tools, Android software for phones, and the Google Pixel phones.

How does this matter for digital advertising?

Google has been collecting data on some two billion people and tens of millions of companies worldwide for twenty years now. Every email you’ve ever sent (including drafts that you deleted), every ad that has ever appeared on your screen, your Android phone movements, air pressure, temperature, and so on, and much more is recorded. Time for a pop quiz: How many Google websites are there? There’s Google Search, Gmail, YouTube, and so on. Perhaps a dozen? Twenty? Forty? There are more than 130 Google websites, and many do not say it’s Google. All of these are collecting data.

AlphaGo Zero looks at that ocean of data on its own to find behavior patterns. It matches behaviors with actions, such as purchases or registration.

Now it becomes interesting. Previous analytics tools (Google and other companies) were like weather reports in the 1970s. They could tell you it rained last week. So what? What’s the weather for the next 30 days? This is important for agriculture, transportation, and many other fields.

Google Analytics 4.0 uses AI to show you future data. It tells you this group will buy in the next seven days. That group will quit your website in the next seven days. Another group will be your top-revenue group in 28 days. This lets you adjust or create new marketing campaigns.

Analytics changes. It’s no more “reports of the past”. It’s actionable future predictions.

The Google Analytics 4.0 data can be imported into Google Data Studio for presentation.

What happens then?

If Google’s AI can find winning patterns in 10¹⁷⁰ data points, what does this mean for marketing? Currently, people enter a few dozen keywords, write a few ads, and manage bids and budgets by hand.

But the Google AI can do this far better. For example, a Responsive Search Ad (RSA) in Google Ads generates over 46,300 permutations. If you place three RSA ads in an ad group, that’s nearly 150,000 ads. Google Ads uses multivariate testing to quickly find the version with the highest click rate. If you have 300 ad groups, that can be forty-five million ads which it uses to find the best ads. Humans can’t do that.

Considering all of this, it’s plausible that within a few years, Google may combine Google Ads, Google Search Console, Google Analytics 4.0, and Google Data Studio into one tool, perhaps called “Google Marketing” which manages marketing on its own.

By Andreas Ramos
Vice President, Digital Marketing
Beasley Direct and Online Marketing, Inc.

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I’ve Come to a New Revelation. We Should Not Accept Bad Email Addresses from List Providers ANY MORE.

I’ve been researching and providing B2B and B2C lists to our clients campaigns for over 27 years. For B2B clients, I’ve used every data provider out there, including D&B, Netprospex, Discover.org, Data.com, OneSource, Lake Group, Hoovers, you name it — and they all have one thing in common: a high percentage (10-20%) of bad data, and even worse, bad email addresses. It’s as though the providers expect us to pay top dollar AND accept a certain percentage of bad email addresses as normal and acceptable. Yeah sure, they’ll replace the bad ones, but by the time you’ve figured out which are bad, the campaign may be long over and your email sending provider (ESP) is hot under the collar from your unacceptable email deliverability rate. Here’s why:

First of All, it’s Getting Harder to Fix the Bad Email Addresses Yourself

It’s become the practice of many marketers to go along with the bad data the providers supply and try to validate or “fix” it themselves by using some kind of a verification tool such as BriteVerify. However, the spam filters are catching on to these verification tools and learning to spoof them by giving false reports or throwing a higher percentage of emails into a catch all bucket, which you shouldn’t mail because they’re not really verified. So you’ve just paid a penny a name or more for validation data you increasingly cannot trust. As a result, it will increasingly bring your email sending domain reputation down by sending to bad email addresses.

Secondly, Improved Database Technology

Secondly, database technology has improved so much with AI and social media verification, that a list vendor literally has no excuse to have inaccurate contact data, let alone bad email data. If they have bad email data, they’re simply not very good at what they do, and they don’t deserve your business.

Lastly, don’t let them be lazy. Make them REALLY validate the data before they supply it to you. Ultimately, that means they have to be creative on their own dime and their own time to figure out if the email addresses are valid.

Finding the Best List Owners

I’ve known some list owners to send a mini survey out on some topic related to your campaign, to see which emails delivered (and which didn’t). This has an added bonus of giving you the response results to the survey. Others have very sophisticated email validation procedures that look at the data from 200+ data points. Bottom line, these list vendors work harder to provide you a good product, and they deserve your business more than the other guys.

You may ask who these mysterious data providers may be. I don’t make it a practice to endorse any vendors in my blog, because they may not offer everyone the same services that they offer me. I have negotiated with my vendors to go the extra mile, do the hard work, and to provide a good product the first time around. And that’s the key. You should negotiate and demand for this level of service from your vendor too.

In conclusion, the time has come for marketers to revolt and not accept bad email addresses from their B2B Data providers ANY MORE.

If you’re in need of quality B2B email lists, our pros can help you. Contact us to find out more.

Read about creating email templates here.

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