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Industry Landscape

The AI/ML platform industry is experiencing rapid growth, driven by increasing adoption of AI across sectors. Key trends include the demand for real-time AI, robust MLOps solutions, and efficient management of large language models. Data sovereignty and ethical AI considerations are also becoming paramount, especially in regulated industries.

Industries:
MLOpsFeature StoreReal-time AIAI LakehouseSovereign AI

Total Assets Under Management (AUM)

Global Artificial Intelligence Market Size in United States

~Approximately $250-300 billion in 2024 (projected)

(35-40% CAGR)

Growth driven by increased enterprise adoption. Strong demand for MLOps and specialized AI solutions. Expansion into new industries and use cases.

Total Addressable Market

Approximately $200 billion

Market Growth Stage

Low
Medium
High

Pace of Market Growth

Accelerating
Deaccelerating

Emerging Technologies

Generative AI & LLMOps

The proliferation of Generative AI models and large language models (LLMs) is driving demand for specialized MLOps platforms capable of managing their unique lifecycle, deployment, and inference challenges.

AI Governance & Explainable AI (XAI)

Increasing scrutiny on AI ethics, bias, and transparency is accelerating the adoption of tools and practices for AI governance, model explainability, and responsible AI development.

Edge AI/Federated Learning

Deployment of AI models closer to data sources at the edge, facilitated by federated learning, is becoming critical for real-time inference, data privacy, and reduced latency in distributed environments.

Impactful Policy Frameworks

EU AI Act (Proposed, Expected 2024)

The EU AI Act is a comprehensive regulatory framework for artificial intelligence, classifying AI systems by risk level and imposing stricter requirements on high-risk AI, including obligations for risk management, data governance, transparency, human oversight, and cybersecurity.

This act will necessitate that Hopsworks provides features and assurances for compliance, particularly for high-risk AI applications, impacting product development and customer deployment strategies.

NIST AI Risk Management Framework (AI RMF 1.0, 2023)

Published by the National Institute of Standards and Technology, the AI RMF provides voluntary guidance for organizations to manage risks associated with AI, focusing on trustworthy AI development and use, including governance, mapping, measuring, and managing risks.

While voluntary, adherence to NIST's framework will become a competitive differentiator, pushing Hopsworks to embed more robust AI risk management and governance tools within its platform.

California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA, 2023)

The CCPA, significantly expanded by the CPRA, grants California consumers more control over their personal information collected by businesses, including rights to know, delete, correct, and opt-out of sharing, and establishes the California Privacy Protection Agency (CPPA).

For Hopsworks, these acts emphasize the critical need for robust data governance, access controls, and data lineage capabilities within its Feature Store and MLOps platform to ensure customer data privacy and compliance.

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