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Machine Learning (ML) Solutions in the US Procurement Price, Data and Insights
The market for Machine Learning (ML) Solutions encompasses products, services, and technologies that leverage machine learning algorithms and techniques to analyze data, make predictions, and enable intelligent decision-making. This includes algorithm development, model training and testing, deep learning, Natural Language Processing (NPL), and computer vision. Typical buyers are large corporations, technology companies, financial institutions, healthcare organizations, retailers, and manufacturing companies. Typical suppliers are technology companies, consulting firms, cloud service providers, machine learning software companies, and data science providers.
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What’s included in this market coverage
IBISWorld's research coverage on the Machine Learning (ML) Solutions procurement and pricing environment in the United States includes market dynamics, buyer power scores, supply chain vendors with pricing trends and forecasts.
About this Market
What’s this procurement report about?
This procurement coverage of the Machine Learning (ML) Solutions market in the United States includes Reinforcement Learning Models, Object Detection Models, Image Recognition Models and Data Analysis Systems. Standard coding in this coverage includes ISIC-582-Software publishing, NACE-58.29-Other Software Publishing, NAICS-513210-Software Publishers and UNSPSC-43230000-Software.
What common market terminology is included?
Common market terminology included in the Machine Learning (ML) Solutions procurement coverage includes Machine Learning (Developing algorithms and models that allow computer systems to enhance their performance through experience without explicit programming instructions.), Bias Mitigation (Addressing biases in generative AI models and training data to promote fairness, diversity, and ethics.), Overfitting (When AI becomes too specialized in training data and does not generate accurate results when encountering new data.) and Training Data (The dataset used to train a generative AI model, consisting of examples and patterns that the model learns from to generate new content.).
What companies are included as top suppliers?
The top companies covered in the Machine Learning (ML) Solutions procurement report as suppliers are Altair Engineering Inc., Alteryx Inc., Sas Institute Inc., Oracle Corporation and International Business Machines Corporation.
Opportunity Assessment
What’s included in the Opportunity Assessment chapter?
The Opportunity Assessment chapter provides a comprehensive market analysis of the Machine Learning (ML) Solutions market in the United States category, including buyer power scoring, market pricing trends, vendor landscape, cost structure, and strategic negotiation levers.
The market pricing trends include the Market Price (2026) per hour, a five year price forecast and a supply chain risk score. Vendor coverage includes a market share and cost structure breakdown.
Analysis includes a comprehensive SWOT analysis of and recent developments impacting the Machine Learning (ML) Solutions market environment.
Buyer Power Score
What’s included in the Buyer Power Score chapter?
The Buyer Power Score chapter assesses key components impacting Machine Learning (ML) Solutions procurement including the recent price trend, forecast price trend, availability of substitutes, switching costs, product specialization, average vendor risk, market share concentration, supply chain risk, price driver volatility and recent price volatility.
These components generate a Buyer Power Score that ranges from -5 (strongly favoring sellers) to +5 (strongly favoring buyers) plus a recommended strategy for procurement specialists.
Price Environment
What’s included in the Price Environment chapter?
The Price Environment chapter covers detailed pricing analysis and datasets on Machine Learning (ML) Solutions market environment. This includes insights into market pricing Market Price (2026), price forecasts, volatility, specialization, substitutes and switching costs.
Datasets in the Price Environment chapter include vendor cost structure, breakdowns of wage rates by geography and specialty, key external economic and labor drivers impacting the market and market pricing models.
Supply Chain & Vendors
What’s included in the Supply Chain & Vendors chapter?
The Supply Chain & Vendors chapter covers the concentration, risk and diversity of the Machine Learning (ML) Solutions market. This includes datasets on the market’s top suppliers, detailed analysis on the key sourcing risks and supply chain dynamics, with environmental, social and governance (ESG) considerations and scores.
Business Requirements
What’s included in the Business Requirements chapter?
The Business Requirements chapter covers vendor relationships, qualifications, service level agreements and key performance indicators. These inputs provide insight into the planning process through the buying lead time, vendor relationship and vendor qualifications. The sourcing process include key RFP elements like an organizational overview, project budget, selection criteria, project schedule, proposal format, inventory control, cost containment, regulation, quality control, distribution and key contract clauses.
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Frequently Asked Questions
What is the current market price for Machine Learning (ML) Solutions?
The 2026 benchmark market price for Machine Learning (ML) Solutions is $78.58 per hour. Prices have increased at a CAGR of 1.43 from 2023-26.
Who are the top vendors in the Machine Learning (ML) Solutions market?
The top vendors in the Machine Learning (ML) Solutions market include Altair Engineering Inc., Alteryx Inc., Sas Institute Inc., Oracle Corporation and International Business Machines Corporation.
What industries supply the Machine Learning (ML) Solutions market?
The top industries supplying the Machine Learning (ML) Solutions market are Computer & Packaged Software Wholesaling in the US and Computer Manufacturing in the US.
What is the supply chain risk for Machine Learning (ML) Solutions?
Low market concentration and fierce competition empower buyers to drive favorable contract terms. The machine learning solutions market features low supplier concentration, with many vendors competing aggressively. This environment gives buyers considerable leverage to negotiate lower prices, enhanced service levels, and contract flexibility. Frequent supplier benchmarking and competitive tenders can yield more cost-effective and innovative solutions. Buyers should capitalize on this fragmented market by encouraging head-to-head supplier bids and demanding commitments to performance, scalability, and customization.
What factors affect the price of Machine Learning (ML) Solutions?
The deployment model of machine learning solutions, such as on-premises, cloud-based, or hybrid, significantly affects pricing due to variations in infrastructure costs, maintenance, scalability, and data security requirements. For example, cloud-based solutions may have lower upfront costs but incur ongoing subscription fees, while on-premises deployments require substantial initial investments in hardware and ongoing IT support, influencing the total cost of ownership for buyers in sectors like finance and healthcare.
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