February 5, 2026

Hackett Group research on contract management

Contract Management and Agentic AI: High Returns, High Risk — How to Navigate Both

Agentic AI, Contract Management, Procurement Technology / By Uday Jain

TL;DR Contract management appears in both the top 5 return areas AND top 5 risk areas for agentic AI. The opportunity: GenAI can translate legalese, extract obligations, and flag compliance issues at scale. The risk: autonomous contract decisions without proper guardrails create legal and financial exposure. Success requires separating AI-assisted analysis from AI-autonomous execution. Organizations […]

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Hackett research on tail spend automation 2026

Autonomous Tail Spend Negotiation: The 86% Opportunity Procurement Is Missing

Agentic AI, Artificial Intelligence, Procurement Technology / By Uday Jain

TL;DR 86% of procurement leaders are likely to consider AI agents for tail spend management. Yet only 36% are satisfied with current tail spend approaches — the largest satisfaction gap in procurement. Autonomous negotiation for low-value, low-risk transactions is the ideal proving ground for agentic AI. Expected improvements of 2-5% on tail spend can translate

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Best Tools for Supply Chain Risk Assessment in 2026

Source-to-Pay, Supplier Management / By Zycus

TL;DR Supply chain risk assessment tools are essential in 2026 as geopolitical uncertainty, supplier fragility, and cost volatility continue to disrupt global operations. Traditional, spreadsheet-based risk tracking is no longer sufficient for complex, multi-tier supply chains. Modern supplier risk software uses AI, real-time data, and predictive analytics to identify, assess, and mitigate risks proactively. Analyst

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Inventory Tracking Programs: From Spreadsheets to Predictive Control

Inventory Tracking Programs: From Manual Spreadsheets to Predictive Control

Procurement Technology, Source-to-Pay / By Zycus

TL;DR Inventory tracking programs have evolved from manual spreadsheets to AI-driven, predictive inventory management software that enables proactive control instead of reactive tracking. Manual and rule-based inventory methods struggle with data accuracy, real-time visibility, scalability, and demand volatility in modern supply chains. Predictive inventory management uses AI and machine learning to forecast demand, optimize reorder

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