By: Gershon Morgulis (Founder & Partner)
Artificial intelligence has become one of the most discussed business topics of the past several years. Organizations across industries are investing heavily in AI tools, while headlines frequently attribute workforce reductions, operational changes, and productivity gains to AI adoption.
But beneath the excitement lies an important question:
Is AI fundamentally changing what businesses can do, or is it primarily making existing capabilities more accessible, efficient, and scalable?
The answer may be more nuanced than many headlines suggest.
The Narrative Around AI and Workforce Changes
Recent discussions in major business publications have highlighted a growing trend: companies increasingly cite AI-driven efficiency when announcing layoffs or restructuring initiatives.
While AI is undoubtedly contributing to operational changes, it is rarely the sole factor behind these decisions.
Many organizations continue to face familiar business pressures, including:
- The need to improve profitability
- Adjustments following pandemic-era hiring expansions
- Higher capital and financing costs
- Increased pressure from investors and stakeholders
In many cases, these factors would have prompted restructuring efforts regardless of AI’s emergence. AI often becomes the most visible explanation, even when broader economic realities are driving the decision-making process.
For business leaders, it’s important to separate the technology itself from the broader business context in which it is being deployed.
Understanding the Economics Behind AI
One aspect of AI that receives less attention is its underlying cost structure.
Despite perceptions that AI automatically reduces costs, today’s leading AI platforms require enormous investments in infrastructure, computing power, and talent.
These systems depend on:
- Massive data center infrastructure
- Significant ongoing computational resources
- Large teams of engineers, researchers, and operational staff
In many ways, AI mirrors other technology platforms that create efficiency through shared infrastructure.
Consider a successful e-commerce business operating through Amazon. On paper, the company may appear exceptionally lean, generating millions in revenue with only a handful of employees. However, much of its operational capability comes from leveraging Amazon’s fulfillment centers, logistics network, and workforce.
The business is not eliminating those costs—it is simply accessing them through a different economic model.
AI may function similarly.
When organizations subscribe to AI platforms or pay usage-based fees, they are often gaining access to substantial infrastructure and expertise that exists outside their own balance sheet. The efficiency is real, but it may be more accurately described as a transfer of operational costs rather than their complete elimination.
Are We Seeing New Capabilities or Better Access?
This leads to a broader strategic question.
How much of today’s AI-driven transformation is truly creating capabilities that were previously impossible?
Many of the most common business applications of AI involve:
- Faster analysis
- More efficient content creation
- Streamlined workflows
- Improved automation
- Better user experiences
These outcomes are valuable, but they are not always entirely new.
In many cases, businesses could achieve similar results using existing automation tools, APIs, integrations, and software platforms. What AI often changes is the level of expertise, time, and effort required to achieve those outcomes.
Rather than introducing entirely new capabilities, AI frequently lowers barriers to entry and makes sophisticated processes available to a broader audience.
That accessibility alone can have a significant impact on competitive dynamics.
Why Speed Changes Everything
Whether AI is creating new capabilities or simply accelerating existing ones, the business implications remain substantial.
When tasks that previously required hours can be completed in minutes, expectations begin to shift.
Organizations quickly adapt to new standards for:
- Decision-making speed
- Customer responsiveness
- Content production
- Operational efficiency
Once these expectations become normalized, businesses that fail to adapt often find themselves at a competitive disadvantage.
Clients begin expecting faster service. Competitors increase productivity. Margins come under pressure for firms that continue operating under older processes.
In this sense, AI’s most disruptive impact may not be the technology itself, but the way it resets expectations across entire industries.
The Reality of AI Pricing
Another common assumption is that AI costs will naturally and continuously decline as adoption increases.
While costs may decrease over the long term, the short-term outlook may be more complicated.
As the market matures, organizations may encounter reduced subsidies from AI providers under increased pressure to monetize AI usage and lower ROI on particular scenarios where AI is now being used.
At the same time, continued advances in hardware, software optimization, and competition will likely drive efficiency gains over the longer horizon.
As a result, both of the following may be true:
- Near-term AI costs could rise as providers pursue sustainable business models.
- Long-term costs may decline as technology and competition evolve.
Business leaders should plan accordingly rather than assuming today’s pricing environment will remain unchanged.
The Strategic Question for Business Leaders
The most important question is not whether AI is revolutionary.
Instead, organizations should focus on understanding where AI creates genuine competitive advantage and where it simply improves access to existing capabilities.
Leaders should evaluate:
- Where AI creates entirely new opportunities
- Which processes benefit most from acceleration and automation
- What costs are being reduced versus transferred
- How competitors are leveraging similar technologies
Regardless of where an organization stands on AI adoption today, one reality is becoming increasingly clear:
The businesses that understand how AI changes expectations—not just capabilities—will be better positioned to compete in the years ahead.
About Imperial Advisory
Imperial Advisory team of CFOs and senior finance executives helps business owners, investors, and leadership teams navigate financial and strategic decisions that drive long-term value. From operational efficiency and growth planning to transaction advisory and business optimization, our team of seasons CFOs provides practical guidance designed to support sustainable success.
About the Author
Gershon Morgulis is the founder and principal of Imperial Advisory. He has provided CFO services for companies across a wide range of industries, acting as an advisor to CEOs and CFOs on issues relating to both day-to-day profitability and long-term strategic growth planning. He has a BA with concentration in Business from Fairleigh Dickinson University and an MBA in Finance with distinction from Hofstra University.