AI Is Everywhere — But Is It Actually Making Businesses More Money?

Artificial intelligence has become one of the biggest technology stories in the world.

Businesses are using AI to write content, analyze information, answer customers, automate repetitive tasks, generate marketing campaigns and increasingly make decisions.

Investment is also exploding.

But there is a question that is becoming harder to ignore:

Is all this AI actually making businesses more money?

That question may be more important than how intelligent the latest AI model is.

Because eventually, every business has to answer the same thing:

What are we getting back for what we're spending?

AI Has Become a Business Priority

There was a time when companies could experiment with AI without knowing exactly where it would lead.

That period is changing.

AI is now being incorporated into marketing, customer service, sales, software development, finance, operations and countless other business functions.

A recent EY survey of 1,200 CEOs across 21 countries found that 50% of CEOs identified AI as the biggest driver of material productivity gains during the previous 12 months.

That sounds like a major success story.

But there is another side to the numbers.

Only 16% of CEOs said they have strong confidence in measuring AI return on investment with real-time visibility into costs and returns. Meanwhile, 23% said AI-driven gains are difficult to convert into measurable financial outcomes.

In other words:

AI may be making people more productive without necessarily making the business more profitable.

And those are not the same thing.

The Trillion-Dollar Question

The scale of AI investment makes this question even more important.

Reuters reported this week that global spending on data centers alone could eventually exceed $30 trillion by 2050, while companies across the AI industry continue committing enormous amounts of capital to infrastructure and development. (StreetInsider.com)

That doesn't necessarily mean the AI boom is a bubble.

It does mean the technology now carries enormous financial expectations.

Investors expect AI to create new products.

Businesses expect it to reduce costs.

Employees expect it to eliminate repetitive work.

Customers expect faster and better services.

And technology companies expect AI to create entirely new markets.

At some point, however, those expectations have to become measurable results.

Productivity Is Not the Same as Profit

Imagine a company uses AI to help its employees complete a task in 30 minutes instead of one hour.

That's a real productivity improvement.

But what happens next?

If employees simply use the extra 30 minutes to do other internal tasks, the company may become more efficient without generating additional revenue.

The situation becomes much more interesting if that saved time allows the company to:

serve more customers
respond to leads faster
launch more campaigns
reduce operational costs
increase sales
provide better customer support
develop new products

That's when productivity can become business value.

EY's latest research makes essentially this distinction: AI can create additional capacity, but companies still have to decide how to redeploy that capacity in ways that create growth.

AI creates possibilities. Businesses still have to turn those possibilities into results.

This Is Where AI Agents Become Interesting

This is also where the evolution from chatbots to AI agents becomes important.

A chatbot can answer a question.

An AI assistant can help create something.

But an AI agent can potentially go further.

It can interact with software, move information between systems, follow instructions and complete multiple steps toward a goal.

That changes the economic equation.

Instead of simply helping an employee work faster, an agent could potentially handle an entire workflow.

For example:

A customer submits a request → the AI responds → qualifies the lead → updates the CRM → schedules an appointment → sends a follow-up → notifies the sales team.

The value isn't just that AI wrote the messages.

The value is that an entire process can potentially require less manual intervention.

And that is a much bigger opportunity.

Business Automation Is Becoming the Real AI Story

This is one reason the next phase of AI may be less about impressive conversations and more about what happens behind the conversation.

The most valuable AI systems may not always be the ones that produce the most spectacular answers.

They may be the ones that quietly remove dozens of small tasks from a company's daily workload.

Think about everything a business does every day:

Customer inquiries.

Lead management.

Appointments.

Marketing.

Follow-ups.

Reviews.

Data entry.

Internal communication.

Reporting.

Payments.

Support.

If AI can connect these processes and perform parts of them automatically, the potential impact becomes much larger than simply having an AI chatbot on a website.

GetResponse: Turning Automation Into Business Results

This is where marketing automation platforms such as GetResponse become particularly useful.

Businesses don't just need AI to generate ideas or answer questions. They also need practical ways to attract potential customers, communicate with their audiences and measure the results of their marketing efforts.

GetResponse offers tools for email marketing, landing pages, contact management and marketing automation that can help businesses organize these activities.

For example, a small business could use a landing page to attract subscribers, send a welcome email, deliver useful information and automate follow-up messages over time.

This doesn't mean every marketing workflow requires an autonomous AI agent. Instead, it shows how businesses can use automation to reduce repetitive tasks and create more consistent customer experiences.

The real opportunity is to connect useful technology with a clear business objective: saving time, nurturing leads and improving the chances of turning interest into sales.

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The Real Test for AI

The AI industry has spent years competing over models, benchmarks and impressive demonstrations.

But businesses have a different scoreboard.

They care about things like:

Revenue.

Costs.

Time saved.

Customers served.

Conversion rates.

Retention.

Profitability.

That means the next stage of AI adoption could become much more practical.

Companies may start asking fewer questions like:

"How advanced is this AI?"

And more questions like:

"How much value does this actually create?"

That's a much harder question.

But it may also be the question that separates useful AI from expensive experimentation.

The Hidden Cost of AI

There is another reason measuring ROI is difficult.

The price of AI isn't necessarily limited to the subscription or API bill.

Businesses may also need to consider:

integration
cybersecurity
employee training
data management
governance
monitoring
process redesign
maintaining old and new systems at the same time

EY specifically highlights these additional factors when evaluating the economics of AI. (EY)

An AI system that costs $500 per month but saves a company $5,000 in productive time could be an excellent investment.

An AI system that costs $500 and creates another layer of complexity may not be.

The technology is the same.

The business outcome is completely different.

The Businesses That May Win

The biggest winners of the AI era may not necessarily be the companies using the most AI.

They could be the companies using the right AI in the right places.

A business doesn't need an AI agent simply because everyone else has one.

It needs one when that agent solves a meaningful problem.

Maybe that's responding to customers faster.

Maybe it's automating lead follow-up.

Maybe it's reducing administrative work.

Maybe it's helping a small team operate like a much larger one.

For example, businesses can use marketing automation tools such as GetResponse to organize email follow-ups, nurture leads and maintain communication with potential customers. The key is to choose tools that solve a real business problem and measure whether they deliver meaningful results.

The important question is not:

"Where can we add AI?"

It's:

"Where is our business losing time, money or opportunities — and can AI fix it?"

That is a much better starting point.

AI Could Still Be the Biggest Productivity Shift in Years

None of this means the AI boom is over.

Quite the opposite.

The technology is still developing extremely quickly.

AI agents are becoming more capable.

AI is gaining access to more applications.

Businesses are connecting AI to their existing workflows.

And companies are experimenting with increasingly autonomous systems.

But the conversation is gradually becoming more mature.

The first phase was about what AI can do.

The next phase may be about what AI can accomplish.

And eventually, businesses will have to measure the difference.

The SpotWonder Take

AI doesn't need to replace every employee to transform business.

It doesn't even need to be perfect.

It simply needs to make certain processes significantly faster, cheaper or more effective.

That's where the real opportunity lies.

The companies that figure this out may gain an enormous advantage.

But companies that adopt AI simply because it is fashionable could discover something else:

More technology doesn't automatically mean more profit.

The real AI revolution may not be measured by how many companies use artificial intelligence.

It may be measured by how many companies learn to turn artificial intelligence into measurable business value.

And that could be the most important AI trend to watch next.

Discover what's worth noticing.

Sources for editorial reference

Reuters — analysis of the enormous investment flowing into AI infrastructure and the financial expectations surrounding the technology. (StreetInsider.com)
EY — October 2026 CEO Outlook on AI productivity, business growth and AI ROI. (EY)

AI Is Everywhere — But Is It Actually Making Businesses More Money?