How AI will make the Contract Manager’s role even more important in the future
This article was written by prof. jur. René Franz Henschel
1: How does AI affect the Contract Lifecycle?
AI will influence the contract lifecycle in several areas:
Analysis of actual contract performance as a function of clause content (e.g., whether a penalty or a bonus affects performance negatively or positively), dependencies (e.g., dependencies across suppliers, markets, geographies), and trends (e.g., market trends affecting contracts, prices, risks, transportation)
Development and selection of the right – and better – contract templates and clauses in the pre-award phase, for example pricing models, incentives, and risk allocation, based on historical data related to the above.
Real-time insights and forecasts on value delivery, opportunities, and risks in individual contracts as well as across contract portfolios.
Adjustment of policies, processes, roles, and responsibilities based on analysis of the above.
Optimization of the entire business and its strategies (procurement, sales, etc.) based on these insights — turning contract management into a strategic tool.
2: How will tasks be distributed between humans and AI going forward?
Humans will continue to take the lead in managing the most complex contracts, particularly those involving substantial development elements or requiring extensive interpretation and professional judgment.
More complex, high-risk contracts will be supported by AI tools for analysis, but negotiation and concrete decisions will remain human tasks.
Medium-complexity, long-term supplier agreements requiring innovation and ongoing collaboration will use AI to analyze trends in contracts, portfolios, and the external environment, as well as monitor compliance with contracts, laws, and policies. Humans will manage relationships and strategic alignment.
For low-complexity contracts with standard clauses and occasional adjustment needs, AI will be able to draft and adapt contracts for daily business use and issue risk alerts. Humans will still review and approve these contracts.
For the lowest-complexity, low-risk contracts, based on standard terms and minimal negotiation, AI will be able to automatically generate contracts and select clauses, based on predefined values and business inputs; AI will also be able to carry out compliance checks.
3: How can AI help improve the areas where value loss is greatest?
Unclear objectives and scope: AI can flag unclear language, inconsistencies between contract and appendices, and suggest rewording and improvements.
Predictive analysis will enable early warnings and recommendations to avoid or mitigate risks, including how best to allocate risk between the parties.
Lack of governance: AI can support and propose improvements to automated workflows, roles, and responsibilities.
Poor negotiation practices: AI can create scenarios that help balance short-term goals and gains with long-term objectives and benefits.
Challenges in handling changes: AI can monitor change requests, analyze commercial and legal consequences, and suggest revised terms and clauses.
AI can support better supplier selection, identify improvement areas, and propose improvement activities.
AI can simplify contract processes and clauses by suggesting fewer and better standards and streamlining procedures.
AI can propose improved clauses to optimize innovation.
AI will help support value measurement through performance benchmarking and identification of contracts that perform better — or worse — than others.
4: How will this affect the Contract Manager’s role and importance?
Contract managers will be able to handle simple and less complex contracts faster and more efficiently, freeing up time and energy for the more complex and highly complex ones.
They will be able to identify contracts needing attention earlier — before issues escalate, e.g., before a quarterly report highlights problems retrospectively.
They will receive support for planning and executing more strategic and balanced negotiations, considering customer/supplier relationships, market conditions, and negotiation context.
They will be able to integrate their work better with ERP and CRM systems, including automatic retrieval of external data to support proactive contract management.
Contract managers can use AI to generate reports identifying, for example, SLA formulations that cause problems and suggestions for solutions. AI can visually illustrate dependencies, connections, and solutions.
Tasks that currently form the core of many contract managers’ daily work — drafting standard low-complexity contracts, preparing contract summaries, performing routine compliance checks, and basic risk analysis following standard protocols — will largely disappear once systems are fully implemented. These tasks must still be monitored and updated regularly.
Contract managers must be adaptable and open to lifelong learning, updating their skills, knowledge, methods, and tools continuously.
Conclusion
Through the use of AI, contract management can become more agile, responsive, and supportive of all areas of the business — including senior management.
Administrative and routine low-value activities can be automated, enabling contract managers to devote more time and energy to developing and optimizing contracts and relationships that carry the highest risks but also hold the greatest potential for organizational value creation.
This evolution — combined with more informed, fact-based decision-making supported by better data — can strengthen human relationships, support knowledge sharing, and elevate the contract management function to a more recognized, strategic role.
As a result, the contract management function may gain greater responsibility, and more contract managers may gain access to leadership levels within their organizations.
Thus, the use of AI in contract management not only enables organizations to better harvest the value embedded in their contracts — it can also enhance the contract manager’s recognition and strategic importance.