VCs predict strong enterprise AI adoption next year — again

Plus: What Are Companies Actually Doing With AI? Our Reporters Talk It Out

Author

Hafizur Rahman
December 29, 2025

In partnership with

Today's Newsletter Highlights:

  • VCs predict strong enterprise AI adoption next year — again

  • What Are Companies Actually Doing With AI? Our Reporters Talk It Out

  • Top 10: Ethical AI Tools

  • Best AI Tools

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VCs predict strong enterprise AI adoption next year — again

Venture capitalists think 2026 will be the year enterprise AI proves its worth and gains widespread use. This is true even with mixed results from early deployments. TechCrunch surveyed 24 VCs focused on enterprises. Most believe next year will be key for AI integration, spending, and results.

🧠 Enterprise AI: From Experimentation to Value

Real results expected in 2026: Investors think many companies have tried AI tools. They think businesses will soon see real ROI and use AI more in their processes.

Budget changes: Budgets may shift from general testing to targeted spending on AI products that show clear, measurable results. Some VCs say a few vendors will capture most of the enterprise AI budget.

Rationalisation of tools: As proof points come up, businesses will drop unnecessary or low-impact tools. They will focus on technology that works well and delivers results. They will shift funds from pilot budgets to formal line-item allocations.

VCs think some companies that built their own systems will move to external AI solutions. They're facing scaling challenges.

What investment is rudimentary for billionaires but ‘revolutionary’ for 70,571+ investors entering 2026?

Imagine this. You open your phone to an alert. It says, “you spent $236,000,000 more this month than you did last month.”

If you were the top bidder at Sotheby’s fall auctions, it could be reality.

Sounds crazy, right? But when the ultra-wealthy spend staggering amounts on blue-chip art, it’s not just for decoration.

The scarcity of these treasured artworks has helped drive their prices, in exceptional cases, to thin-air heights, without moving in lockstep with other asset classes.

The contemporary and post war segments have even outpaced the S&P 500 overall since 1995.*

Now, over 70,000 people have invested $1.2 billion+ across 500 iconic artworks featuring Banksy, Basquiat, Picasso, and more.

How? You don’t need Medici money to invest in multimillion dollar artworks with Masterworks.

Thousands of members have gotten annualized net returns like 14.6%, 17.6%, and 17.8% from 26 sales to date.

*Based on Masterworks data. Past performance is not indicative of future returns. Important Reg A disclosures: masterworks.com/cd

What Are Companies Actually Doing With AI? Our Reporters Talk It Out

Workflow automation: Companies are using AI to automate routine tasks. This includes summarising documents, processing emails, and extracting insights from internal data.

Content and Service Support: Tools like Microsoft Copilot help create internal documents, answer customer questions, and perform basic analytics.

Customer-facing improvements: AI agents are being tested as support chatbots. Most still need human supervision and oversight.

🏢 Boilerplate vs. cutting edge

  • Many companies seek simple gains. They want better efficiency, quicker admin tasks, and automation of desk jobs. They often avoid major changes to their business models.

  • Only a few companies, like Walmart, Nvidia, and some banks, are using AI more deeply. They employ agents and custom systems to enhance backend workflows and analytics.

  • Even where AI is in use, ROI often isn’t just financial. Time savings, cost avoidance, and quicker decision-making are often noted as key benefits.

Top 10: Ethical AI Tools

1) Microsoft Responsible AI Toolbox – Comprehensive ethical AI suite

An open-source toolkit helps with fairness checks, understanding, and error analysis in AI development. It's popular for enterprise model development and governance.

2) IBM watsonx.governance – Enterprise governance and guardrails

IBM's watsonx platform includes this tool. It offers solid oversight, identifies bias, and ensures compliance for foundation models in complex business settings.

3) Google Responsible Generative AI Toolkit – Safe GenAI development

Provides guidance, safety practices, model cards, and developer tools. This ensures transparency and ethical practices in building generative AI apps.

4) Amazon SageMaker Clarify – Bias detection & explainability

AWS SageMaker includes tools that help spot and reduce bias. They also explain how models work and boost transparency during training and deployment.

5) Salesforce Ethical AI / Einstein Trust Layer – Customer data protection and ethical guardrails

This layer, part of Salesforce’s AI services, keeps customer data safe and ensures compliance in AI-driven CRM processes.

6) SAP AI Ethics / Compliance – Enterprise governance and ISO-level assurance

SAP’s ethics framework covers compliance with global standards (like EU AI Act) and includes a dedicated AI Ethics Office and policies.

7) Credo AI – Governance & Trust OS

A governance platform that aligns AI systems with regulations like the EU AI Act and NIST RMF. It also creates auditable oversight using trust scoring and risk registries.

8) TruEra AI Observability – Model quality & bias analysis

Now part of Snowflake, TruEra provides root-cause analysis for ML and LLMs. This helps debug performance and bias issues, building trust in predictive systems.

9) Collibra AI Governance – Unified data & AI lineage oversight

A governance platform tracks data and AI use from start to finish. It helps businesses trust their inputs and outputs while keeping their data's pedigree intact.

10) Monitaur – Regulated industry governance

Focuses on governance for financial and insurance firms. It helps scale AI projects while ensuring compliance and managing regulatory risks.

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