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The New Deal Team: What 1,000 Dealmakers Reveal About AI-Driven M&A

AI is no longer an edge in M&A, it is becoming the baseline. Datasite surveyed 1,000 senior dealmakers, backed by in-depth interviews with M&A leaders, to reveal how AI is reshaping every stage of the deal, and where human judgment still decides the outcome. See where your peers are placing their bets and how the modern deal team is being built.

Inside the report, you will learn:

The deal stages where AI is already fully embedded, led by due diligence and sourcing
Why 62% of dealmakers now call human-only decisions indefensible on complex deals
The decisions that stay human, from final sign-off to reading the room with a founder
How top firms build accuracy, security, and governance into AI-assisted dealmaking
What the next deal team looks like as AI handles the prep and people close the last mile

How to Evaluate AI Vendors for Your Legal Team

AI tools are entering legal workflows faster than most firms can vet them. Contract review, e-discovery, compliance monitoring - the use cases are real, but so are the risks. Confidentiality gaps, unreliable outputs, and tools that can't adapt to your specific playbooks can set your team back instead of moving it forward.

This guide gives legal teams a structured evaluation framework covering six critical areas - so you can ask the right questions before you commit.

What you'll learn:

How to assess whether a tool adapts to your firm's policies, escalation rules, and precedents
What accuracy benchmarks and error-tracking standards to require
Key governance and ethics questions including bias audits and audit rights
Integration requirements that determine real-world adoption
How to tie AI selection to defined legal outcomes - not vague productivity gains
ROI evidence and scaling criteria to validate before expanding beyond a pilot

Is Your Contract Review Process Ready for What’s Next?

In-house legal teams are being asked to handle more contracts, faster, without adding headcount. The result: inconsistent redlines, institutional knowledge that lives only in senior counsel's heads, and a constant tradeoff between speed and accuracy.

This toolkit from Filevine helps legal operations leaders diagnose where their contract review process is falling short — and what modernization actually looks like in practice.

What you'll get:

A breakdown of the four hidden costs teams face when they try to scale contract review manually
A 24-point self-assessment checklist covering volume, urgency, consistency, workflow, AI readiness, and business impact
A scoring framework to benchmark where your team stands today
A clear picture of what domain-specific AI looks like when it's built directly into Microsoft Word — not bolted on as a separate platform

Built for General Counsel, legal ops leaders, and contract teams navigating growing workloads with flat resources.

Close the Personalization Gap in Your External Training

Personalization works for employees because the system already knows them. The moment you train distributors, resellers, partners, and customers, that breaks. Roles are unclear, knowledge levels vary widely, and no one is obligated to finish.

This guide shows why employee-first LMS platforms fall short in external training, and what a platform built for the extended enterprise does differently to keep partners and customers engaged.

What you'll learn:

Why personalized pathways break down once learners sit outside your organization
Where rule-based logic, manual segmentation, and internal recommendation engines hit a wall at scale
The hidden costs of an employee-first LMS: admin overhead, localization delays, and learner drop-off
What adaptive learning looks like at scale, from diagnostic entry points to role-based storefronts and AI-supported delivery

Close the Personalization Gap in Your External Training

Personalization works for employees because the system already knows them. The moment you train distributors, resellers, partners, and customers, that breaks. Roles are unclear, knowledge levels vary widely, and no one is obligated to finish.

This guide shows why employee-first LMS platforms fall short in external training, and what a platform built for the extended enterprise does differently to keep partners and customers engaged.

What you'll learn:

Why personalized pathways break down once learners sit outside your organization
Where rule-based logic, manual segmentation, and internal recommendation engines hit a wall at scale
The hidden costs of an employee-first LMS: admin overhead, localization delays, and learner drop-off
What adaptive learning looks like at scale, from diagnostic entry points to role-based storefronts and AI-supported delivery

State of Context Management Report 2026

DataHub commissioned independent research firm TrendCandy to survey 250 IT and data leaders about the state of context management in 2026. The findings reveal a market at an inflection point: high confidence, real infrastructure gaps, and a correction already underway.

What you'll learn:

Why organizations that self-assess at the highest stage of context management maturity still struggle with the fundamentals
How “good enough” context solutions that work in pilots consistently break down at production scale
Why 83% of IT and data leaders now believe agentic AI cannot reach production value without a dedicated context platform
What the surge in context management infrastructure investment reveals about where the market is heading
The three imperatives for data and IT leaders in 2026

Unlocking AI’s Potential Through Context Management

Context engineering was supposed to solve AI’s scalability challenges. Teams are building RAG pipelines, crafting prompt templates, and implementing memory systems—each application starting from scratch. As AI scales organization-wide, these tactical approaches hit fundamental limits: fragmented systems, inconsistent outputs, and no organizational context intelligence.

This keynote explores the essential building blocks of an enterprise context platform and introduces context management as the emerging discipline that changes how organizations approach this challenge.

Key Takeaways:

Understand the fundamental differences between metadata for humans and context for AI agents
Learn why current context engineering approaches create compounding technical debt that kills enterprise AI scaling
Discover the emerging architectural pattern that transforms context from bottleneck to competitive advantage
Explore the transformative possibilities that context management will unlock for enterprise AI

State of Context Management Report 2026

DataHub commissioned independent research firm TrendCandy to survey 250 IT and data leaders about the state of context management in 2026. The findings reveal a market at an inflection point: high confidence, real infrastructure gaps, and a correction already underway.

What you'll learn:

Why organizations that self-assess at the highest stage of context management maturity still struggle with the fundamentals
How “good enough” context solutions that work in pilots consistently break down at production scale
Why 83% of IT and data leaders now believe agentic AI cannot reach production value without a dedicated context platform
What the surge in context management infrastructure investment reveals about where the market is heading
The three imperatives for data and IT leaders in 2026

Unlocking AI’s Potential Through Context Management

Context engineering was supposed to solve AI’s scalability challenges. Teams are building RAG pipelines, crafting prompt templates, and implementing memory systems—each application starting from scratch. As AI scales organization-wide, these tactical approaches hit fundamental limits: fragmented systems, inconsistent outputs, and no organizational context intelligence.

This keynote explores the essential building blocks of an enterprise context platform and introduces context management as the emerging discipline that changes how organizations approach this challenge.

Key Takeaways:

Understand the fundamental differences between metadata for humans and context for AI agents
Learn why current context engineering approaches create compounding technical debt that kills enterprise AI scaling
Discover the emerging architectural pattern that transforms context from bottleneck to competitive advantage
Explore the transformative possibilities that context management will unlock for enterprise AI

AI Is Live In Production. Is Your Identity Stack Ready?

AI agents, copilots, and AI-powered features are already touching customer data and internal systems. Yet 88% of leaders say their identity and security infrastructure is behind, and the most confident teams report the most incidents.

The 2026 State of AI and Identity Report draws on responses from more than 300 technology and security leaders to show where that gap turns into real risk, and what the teams who contain it do differently.

In this report, you will learn:

Why identity risk spikes when AI moves from pilot to pervasive use
How the confidence-reality gap leaves mature-looking organizations exposed
Why comprehensive policies and processes are not enough on their own
How leading teams rethink deployment, isolation, and machine identity
The 9 architecture questions to ask any identity vendor

The EHS Leader’s Guide to Safety System Modernization

Legacy safety systems create blind spots that slow down reporting, fragment data, and leave your teams reacting to incidents instead of preventing them.

This guide from Intelex gives EHS leaders a clear framework for evaluating their current system and understanding what a modern safety platform should deliver.

In this guide, you will learn:

The key warning signs your safety system has blind spots, from manual compliance tracking to limited real-time visibility
What a modern safety system should deliver across eight critical capabilities, including mobile reporting, automated workflows, and real-time dashboards
The cost of doing nothing, with OSHA fines up to $165,514, average injury costs of $40,000, and unplanned downtime at $220K per hour
How to build the ROI case for modernization with data-backed benchmarks from Verdantix research

Creating and Sustaining a Safety Culture

Every organization wants a safe working environment. But there is a gap between having a safety strategy and having a culture where employees live and breathe safety in how they work every day.

This mini-guide from Intelex gives EHS leaders a practical framework for closing that gap and building a safety culture that sticks.

In this guide, you will learn:

Why even robust safety strategies fail when culture is not aligned and how to bridge the gap
How leadership sets the tone for safety culture and why accountability must start at the top
Why safety communication must focus on the why as much as the how to drive real behavior change
The five building blocks of an effective safety culture: compliance, capability development, communication, management involvement, and measurement

The EHSQ Field Guide for Pharmaceuticals

In pharma, compliance challenges rarely stem from a single issue. Fragmented systems make it hard to trace work end-to-end, and when teams treat incidents, audits, and CAPAs as isolated tasks, problems get fixed locally instead of reduced across sites.

This guide from Intelex walks through seven scenarios pharma EHSQ teams face and shows how connecting safety, quality, and operations changes the outcome.

In this guide, you will learn:

How to manage incidents that become quality deviations without creating conflicting records
Why compliance processes break down when auditors arrive and how to fix it
How to handle Management of Change so improvements do not introduce new risk
How to standardize reporting across global sites while respecting local regulations
Ways to turn audit findings into preventive action instead of repeating fixes site by site

2026 EHS Trends and Priorities: What Energy Sector Leaders Need to Know

New research from Intelex reveals where EHS is headed - and what it means for energy companies navigating AI adoption, tighter regulations, and a shifting workforce.

Based on a survey of 864 senior EHS professionals across North America and Europe, this report delivers sector-specific benchmarks and actionable insights for 2026.

In this report, you'll learn:

How executive engagement in energy compares to other industries and why it matters for EHS effectiveness
The safety culture approaches gaining traction - including a 42% higher rate of peer-to-peer accountability in energy
Where AI and IoT are driving real improvements and where implementation challenges remain
What 75% of respondents say about the growing EHS talent shortage and the skills they need next

2026 EHS Trends and Priorities: What Manufacturers Need to Know

New research from Intelex reveals where EHS is headed - and what it means for manufacturers navigating AI adoption, tighter regulations, and a shifting workforce.

Based on a survey of 864 senior EHS professionals across North America and Europe, this report delivers manufacturing-specific benchmarks and actionable insights for 2026.

In this report, you'll learn:

Why manufacturing leads other industries in executive EHS engagement at 73% and how to sustain it
The safety culture approaches gaining traction - with 46% of manufacturers relying on mandatory protocols
Where AI and IoT are driving real improvements and where implementation challenges remain
What 85% of manufacturing respondents say about workforce engagement as the top ROI driver