Latest AI (Artificial Intelligence) News

đź“…January 15, 2026 at 1:00 PM
AI surges as top global risk, unlocks trillions in productivity, advances drug discovery and industry, while sparking trust alliances and scientific exploration debates.
1

AI Climbs to No. 2 Global Business Risk in Allianz Risk Barometer

Cyber risks top the 2026 Allianz Risk Barometer for the fifth year, but AI jumped from No. 10 to No. 2 (32% of responses), reflecting operational, legal, and reputational concerns amid rapid adoption outpacing governance.Source 1 Allianz notes AI's interlinks with cyber, political, and regulatory risks, with quantum computing breakthroughs feared as a black swan event by 19%.Source 1 Business interruption fell to No. 3.Source 1

2

AI Reshapes Drug Discovery by Accelerating Key Steps

AI is transforming drug discovery by speeding up target identification, compound generation, and safety prediction in complex human biology.Source 2 In ADPKD research, AI simulations and data mining identified dozens of gene candidates, validated in lab organoids within a year.Source 2 For Huntington’s, generative AI designed 15 million compounds, leading to potent brain-penetrant degraders after testing just 60.Source 2

3

Thomson Reuters Launches Trust in AI Alliance with Top Players

Thomson Reuters Labs convened Anthropic, AWS, Google Cloud, and OpenAI in the Trust in AI Alliance to define principles for trustworthy agentic AI systems.Source 3 The group focuses on safety, accountability, and transparency in high-stakes environments, sharing insights publicly.Source 3 First session targets engineering trust into professional AI architectures.Source 3

4

Siemens Unveils Industrial AI Tech at CES 2026

Siemens showcased AI-powered digital twins with NVIDIA, enabling PepsiCo to simulate factories with 90% issue detection, boosting throughput 20% and cutting Capex 10-15%.Source 4 In life sciences, Dotmatics acquisition integrates data for AI-driven drug discovery, potentially halving therapy timelines.Source 4 CEO Jensen Huang calls it a new industrial revolution fusing software and AI.Source 4

5

Cognizant Report: AI Can Unlock $4.5 Trillion in US Labor Value

New Cognizant research shows AI could automate or assist tasks worth $4.5 trillion in US labor productivity today, adding $1 trillion to GDP.Source 5Source 7 AI exposure in jobs has risen 30% faster than 3-year-old forecasts, now at 9% annual growth.Source 5 Businesses must align investments via three key actions for maximum impact.Source 5

6

Debate Intensifies: Can AI Generate Truly New Ideas?

Recent analyses highlight AI accelerating science by suggesting novel hypotheses, like narrowing 50 options to 5 in experiments, though not independently discovering.Source 6 Breakthroughs include AlphaGenome for diseases, robot dexterity, and weather forecasting.Source 6 Concerns persist on reinforcing paradigms over challenging them.Source 6

7

AI Supercharges Scientists but Narrows Collective Exploration

Analysis of 41 million papers shows AI expands individual capabilities yet concentrates research on data-rich areas, creating 'lonely crowds' with overlapping work.Source 8Source 10 Scientists migrate to measurable benchmarks, shrinking knowledge extent.Source 8Source 11 Authors urge AI to expand data creation, not just analysis, for sustainable advances.Source 8

8

CEOs Lead AI Surge, Planning to Double 2026 Investments

BCG reports companies will double AI spending in 2026 to 1.7% of revenues, with 94% continuing investments despite costs; CEOs spend 8+ hours weekly upskilling.Source 9 Leaders invest twice as much in organizational AI capabilities.Source 9 Optimism persists on ROI.Source 9

9

2026 Shapes Up as Big Year for AI in Structural Proteomics

AI enables next-gen breakthroughs in structural proteomics, building on computing advances for drug discovery successes.Source 12 The year promises continued momentum in AI-driven biotech innovations.Source 12

10

TDWI Predicts Top 12 AI, Analytics Trends for 2026

TDWI forecasts include API-first approaches, microservices shifts, and omnichannel prioritization to leverage AI in data and analytics.Source 13 Emphasis on heterogeneous compute for diverse enterprise AI workloads.Source 14 Trends signal pragmatism over hype.Source 6