Retail AI isn’t just moving fast—it’s warping the very fabric of how business decisions are made. From dynamic pricing to predictive forecast management, artificial intelligence has become a necessity for businesses striving to remain competitive. Yet, while the benefits of AI are undeniable, one major decision looms over retailers: should they build their own AI solutions or buy AI-powered services?
According to Forrester’s AI Pulse Survey, the answer is clear. Most business organizations, especially in retail, eCommerce, and omni-channel sectors—are choosing to adopt AI by purchasing subscription-based or embedded AI solutions rather than investing in the time-consuming and costly process of building their own.
Why? Because building AI from scratch isn’t just challenging, it’s an uphill battle that most retailers simply can’t afford to fight.
The Illusion of Building AI In-House
On the surface, developing an AI model internally may seem like a good way to tailor a solution to a company’s unique needs. Especially if your IT department has its own data science team. But reality is far more complex and often times those teams are tied up with projects that have timelines and roadmaps that are years out or no end in sight.
To create an AI system that can truly deliver competitive insights, price optimization, or promotional effectiveness, retailers need a sophisticated blend of:
Strong data exports – AI thrives on data, and retailers must collect, clean, and structure an enormous amount of competitive pricing, customer behavior, and inventory data before AI can even begin learning.
Top-tier talent – Data scientists, machine learning engineers, and AI specialists are in high demand and come with hefty salaries.
Years of development – Training, testing, and refining AI models is an ongoing, resource-intensive process.
Robust infrastructure – AI models require powerful cloud computing resources to function at scale, which adds to operational costs.
Even retail giants with deep pockets struggle with these challenges. Smaller and mid-sized retailers? They rarely stand a chance to build this on their own. In fact, we’ve not come across one yet.
Retailers Need AI Now—Not Years from Now
Retail is an industry driven by immediacy. Pricing changes daily. Competitor strategies shift rapidly. Consumer behavior evolves in real time. Any delay in decision-making can cost millions in lost revenue.
For example, a fashion brand that lacks AI-driven pricing insights may find itself undercut by competitors during a crucial season relative to what they are selling, missing out on potential profits. Similarly, a grocery chain that fails to analyze competitor promotions could miscalculate its own discounts, leading to unnecessary margin erosion.
Competitor AI and Pricing AI from Hypersonix provide retailers with calculated insight into pricing moves, competitor strategies, and promotional effectiveness—without the years of development required to build such capabilities internally. These algorithms are built for the commerce industry’s roller coaster ride of market trends, fierce competition, and fluctuating customer demands.
These AI-powered tools use:
Machine learning algorithms to track and predict competitor pricing patterns.
Computer vision and LLM-based product matching to identify equivalent products, including private-label alternatives.
Dynamic pricing engines that optimize prices based on demand elasticity, competitive movements, and margin targets.
By leveraging subscription-based AI solutions, retailers can implement cutting-edge capabilities immediately, instead of waiting years to develop their own models.
The Cost Factor: Building vs. Buying AI
Beyond time constraints, the cost of building AI in-house is staggering. Developing a single, fully functional AI model can require millions of dollars in research, development, and ongoing maintenance.
Consider this:
The median salary for a machine learning engineer is $150,000+ per year—and most AI teams require dozens of specialists.
Cloud computing and data infrastructure can cost millions annually to support AI model training and deployment.
Data collection and labeling (essential for AI training) can take months, if not years, to complete effectively.
Even if a retailer manages to build an AI model, the work doesn’t stop there. AI requires constant updates, retraining, and model fine-tuning to remain effective as the market evolves. You also need a strong retail business mind to work with and communicate use cases to the team of data scientists and engineers. What is really important to remember, is Forrester’s survey responders were tech decision makers, suggesting they already know the cost of building retail optimization tools for their merchandising, marketing, and analysts is out of reach.
On the other hand, purchasing an AI-powered subscription solution like Hypersonix AI gives retailers access to:
Updates on competitors, pricing, promotions, and forecasting insights.
Automated price optimization models that adapt in real time.
Advanced product-matching capabilities that provide a complete view of the competitive landscape.
Predictive AI models that anticipate pricing trends and customer demand shifts.
All of this—without the massive upfront investment or ongoing maintenance required to build AI from scratch.
AI as a Competitive Advantage in Retail
Retail is no longer a game of guesswork. The businesses that succeed in today’s market are those that harness AI to drive real-time, data-backed decisions.
Companies like Amazon, Walmart, and Target already leverage AI to dynamically adjust pricing, optimize promotions, and predict customer demand. Smaller and mid-sized retailers can now access the same level of intelligence by purchasing AI solutions instead of building them.
Hypersonix AI’s Pricing AI and Competitor AI offer the plug-and-play intelligence that retailers need to:
Outmaneuver competitors with precise and timely pricing strategies.
React faster to market shifts without manual intervention.
Maximize revenue and margins through AI-driven insights.
The future of AI in retail isn’t about who can build the best model—it’s about who can deploy AI-powered intelligence the fastest.
And for most retailers, buying AI is the only real path to staying competitive.
Final Thoughts: The Smarter Move? Buy, Don’t Build
The Forrester AI Pulse Survey confirms what the retail industry already knows: Building AI in-house is a luxury that few can afford. Retailers who try to develop their own AI solutions risk falling behind in an industry that moves at lightning speed.
Instead, forward-thinking retailers are turning to Pricing AI, Competitor AI, and Promo AI to gain immediate, scalable, and cost-effective AI-powered capabilities.
Why spend years and millions of dollars building AI when you can start optimizing your pricing and promotions today?
The smarter path is evident, and now we understand why Forrester’s survey respondents answered as they did.
