Thursday, October 15, 2026
Source trace. Via News points to the documents behind its reporting and shows what we drew from each — so you can check any claim. How we source
News articleMIT Technology Review

Scaling AI agents with trustworthy data

View original at technologyreview.com
MIT Technology Review - Ai Research Title: Scaling AI agents with trustworthy data Date: 2026-08-12 16:51 Source: https://www.technologyreview.com/2026/08/12/1141032/scaling-ai-agents-with-trustworthy-data/ <p>Business and technology leaders need no convincing that the time of agentic AI is here…
Opening lines of the source · MIT Technology Review · short snapshot — read the full document at the original

What we drew from this source

The claims Via News extracted from this document. We point to the source; we don't replace it.

  • AI agents will augment or automate 50% of business decisions by 2027.

    60% confidence
  • Within two years, 100% of respondents plan to be using agentic AI, with 69% expecting to use it widely.

    60% confidence
  • In organizations categorized as 'data laggards', AI access to company data falls to 30% or less.

    60% confidence
  • Two-thirds of data laggards say legacy data systems limit AI agent scaling (66%) and prevent agents from making decisions at speed (68%), versus just 8% of data leaders reporting either constraint.

    60% confidence
  • Only around half of surveyed organizations trust that the decisions their AI agents make are accurate and relevant, whereas 100% of data leaders trust their agents' decisions.

    60% confidence
  • Across all surveyed organizations, AI only has access to an average of 45% of company data.

    60% confidence
  • A select group of 'data leaders' ensures access to over 70% of their data and has greater success with agents.

    60% confidence
  • The most important initiative to enable scaling among all respondents is improving access to structured and unstructured data for AI agents, followed by enhancing data and AI governance with business context; data leaders are also focusing heavily on automation of data management.

    60% confidence

Cited in these Via News reports

What we know · the intelligence behind this page
Live from the substrate
What we're seeing
Q4 2026 Biopharma Catalyst Cluster: Late-Stage Readouts and Regulatory Milestones
October 2026 brings a dense run of Phase 3 wins (ALOFT-IPF, RESTORE-3), new data presentations (Roche, Bayer, Lilly, Vertex, Galderma) and regulatory steps (FDA acceptance of Roche's vamikibart BLA, Scholar Rock's EMA resubmission). The next big catalyst is the ivonescimab FDA PDUFA date on 2026-11-14. Obesity combination studies (REDEFINE 4, TOGETHER-PsO) and the 2027 Maritime-1 completion point to more catalysts ahead. QAIAx's speculative AI-linked trial claims (the QIII pilot, targeted for 2027) are an unrelated micro-cap sideshow with weak evidence, and have little in common with the large-cap pipeline news.
Our read on the data ›
Signals we're tracking
EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
Patterns we're watching ›
Where sources disagree
ING Group
Both facts record the same metric (shares_outstanding) for ING Group at the identical observation date (2025-12-31). FACT A states 2,902,437,688 shares; FACT B states 2,902 million shares (2,902,000,000). The difference is 437,688 shares (~0.015%). This is a genuine value conflict, though the discrepancy appears to result from FACT B rounding to the nearest million while FACT A provides the precise count.
We flag conflicts openly ›
Recently verified
✓ Checked against the original source
4,986
facts traced to their source — and we flag the ones that don't hold up.
101 entities tracked4,986 facts checked against source5,377 source documents archived
Query this data → isubstrate.com