AI Market Research – SIS International

人工智慧市場研究

AI Adoption Research for Enterprise Buyers, Not Vendor Hype

SIS studies how enterprises are actually deploying AI: which vendors they are selecting, what they are spending, where deployment is stalling, and which regulatory requirements are shaping procurement decisions. Research covers the EU AI Act, the NIST AI Risk Management Framework, and sector-specific compliance mandates.

The focus is commercial adoption. Not press releases.

Enterprise Procurement Patterns

Which AI vendors are winning enterprise contracts and why. SIS interviews IT decision-makers and procurement officers to map vendor selection criteria, contract structures, switching costs, and build-versus-buy decisions across verticals including financial services, healthcare, and manufacturing.

Deployment ROI and Stall Points

Where AI deployments are delivering measurable returns and where they are stalling. SIS captures ground-truth data from CTOs and data science directors on integration timelines, infrastructure costs, model accuracy in production, and the gap between pilot results and scaled performance.

AI Product Usability Testing

SIS runs usability sessions at our Flatiron District facility and online to test AI-powered interfaces: copilots, chatbots, recommendation engines, and generative tools. Research measures task completion, error recovery, trust calibration, and the gap between user expectation and model output.

Infrastructure and Supply Chain

GPU supply constraints, cloud compute pricing, data center capacity, and the semiconductor dependencies behind large model training. SIS tracks how NVIDIA allocation, hyperscaler capacity planning, and the CHIPS Act are shaping AI infrastructure investment decisions through interviews with procurement and engineering leaders.

競爭情報

Named competitor tracking for AI vendors: product roadmaps, pricing changes, API ecosystem development, partnership announcements, and patent activity. SIS monitors public filings, conference proceedings, and developer community signals. Triangulated with expert interviews to separate announced capability from shipping product.

Regulatory Compliance Research

The EU AI Act classifies systems by risk tier and imposes conformity assessments on high-risk applications. The NIST AI RMF provides a voluntary governance framework adopted by U.S. federal agencies. SIS tracks how these frameworks, plus sector-specific mandates (FDA for clinical AI, EBA for financial services), affect enterprise procurement timelines and vendor qualification.

SIS International – AI Market Research & Strategy Consulting

ENGAGEMENT TYPE 01

VENDOR EVALUATION AND PROCUREMENT

Which AI Vendors Are Winning Enterprise Contracts, and Why

SIS interviews CIOs, CTOs, and procurement officers at enterprises evaluating AI platforms. Research covers vendor selection criteria, contract structures, total cost of ownership, integration complexity, and build-versus-buy decisions. Recent engagements have mapped procurement patterns for generative AI tools in financial services and computer vision systems in manufacturing quality control.

ENGAGEMENT TYPE 02

COMPETITIVE INTELLIGENCE

Track Competitor AI Strategy Through Filings, Patents, and Field Research

SIS monitors named AI competitors through SEC filings, patent databases, developer conference proceedings, API changelog analysis, and pricing page changes. Expert interviews with engineers, product managers, and channel partners who interact with the competitor’s product add context that public data cannot. The output separates announced capability from shipping product.

ENGAGEMENT TYPE 03

MARKET SIZING AND GO-TO-MARKET

Size the Market Before You Commit to Scale

SIS builds bottom-up market sizing models for AI products through interviews with target buyers. Research quantifies willingness to pay, adoption timelines, and switching costs in specific verticals. Go-to-market planning includes channel analysis, pricing strategy, and regulatory readiness assessment covering the EU AI Act risk tier system and NIST AI RMF governance requirements.

WHY SIS FOR AI RESEARCH

Primary Research, Not Secondary Analysis

Most AI market reports repackage vendor press releases and analyst estimates. SIS interviews the enterprise buyers making the actual procurement decisions. The difference is the difference between what vendors claim and what customers confirm.

Interviews with Enterprise Buyers, Not Vendor Briefings

SIS conducts 15 to 20 structured interviews per engagement with CIOs, CTOs, data science directors, and procurement officers. These are 45- to 60-minute conversations with the people who sign AI contracts, not the vendors selling them.

Named Regulatory Frameworks, Not Vague Compliance Talk

SIS tracks the EU AI Act (risk tier classification, conformity assessments for high-risk systems), the NIST AI RMF (governance framework adopted by U.S. federal agencies), FDA requirements for clinical AI, and EBA guidelines for financial services AI. Research explains how each framework affects procurement timelines.

Usability Testing at Our NYC Facility

SIS runs AI product usability sessions at 11 East 22nd Street in Manhattan and online. Research tests copilots, chatbots, recommendation engines, and generative interfaces with recruited end users. Metrics include task completion rate, error recovery, trust calibration, and the gap between user expectation and model output.

40 Years of Research Methodology Applied to AI

SIS has conducted primary research across 135 countries since 1984. The same methodology that Ruth Stanat built for competitive intelligence, market entry, and Voice of the Customer programs now applies to AI adoption research. The interviewers are trained researchers, not technology evangelists.

THE SIS DIFFERENCE

我們的服務包括：

AI Adoption Research for Enterprise Buyers, Not Vendor Hype

Six Areas of AI Intelligence

Enterprise Procurement Patterns

Deployment ROI and Stall Points

AI Product Usability Testing

Infrastructure and Supply Chain

競爭情報

Regulatory Compliance Research

Three Research Engagements for AI Decision-Makers

Primary Research, Not Secondary Analysis

Recommended

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