Contracting has been digitised. So why does it still feel manual?

Despite millions invested in CLM and AI, contracting functions continue to operate much as they always have. CLM systems have been implemented, templates standardised, and workflows digitised. Yet in many organisations, the process still feels slow, inconsistent, and overly dependent on manual intervention.

This is not a failure of technology, but a failure to re-engineer how contracting operates as a system. The result is a model that appears modern on the surface while continuing to operate like a manual process underneath.

The Core Problem: Contracting is Still Treated as Legal Work

In many organisations, contracts are still treated as individual pieces of legal work, with documents drafted, reviewed, negotiated, approved, executed, and filed. The relationship between the business and legal remains fundamentally transactional, with legal teams continually grappling with increasing work volumes, challenging deadlines, and constrained budgets.

At scale, contracting functions have to be more like an operational infrastructure rather than a series of isolated tasks. They sit at the centre of revenue generation, procurement efficiency, risk management, and compliance. When contracting is treated as infrastructure:

• Speed and deal velocity become commercial levers, not just legal KPIs
• Consistency becomes a control mechanism, not simply a preference
• Data becomes an asset, not a by-product

Digitised Inefficiency: Where Most Teams Stall

In less mature contracting environments, the same patterns repeat:

• Intake quality varies significantly
• Standard templates are frequently bypassed or heavily rewritten
• Negotiation positions shift depending on the individual lawyer involved
• Routine work is escalated unnecessarily
• Visibility into cycle time, deviations, and outcomes remains limited

By contrast, high-performing contracting functions operate with discipline:

• Intake is structured and controlled at source
• Contract types are clearly segmented by risk and complexity
• Playbooks are embedded and consistently applied
• Negotiation boundaries are clearly defined and enforced
• Performance is measured, not assumed
• Data is captured in a consistent and usable format

The difference is not the tooling; it is operating model design.

The Real Shift: From Workflow Efficiency to Decision Engineering

Many legal teams remain focused on optimising workflows to improve speed, reduce handoffs, and shorten turnaround times. That matters, but it is not enough.

The real constraint in contracting is not process execution, but inconsistent decision-making. Every deviation, renegotiation, and review cycle stems from the same decisions being recreated repeatedly, whether around liability caps, indemnity provisions, approval thresholds, or acceptable fallback positions. The next evolution lies in moving from workflow automation to decision engineering, where AI becomes genuinely transformative.

Where AI Actually Adds Value

AI is not about replacing lawyers or automating entire negotiations. Its value is far more practical, and considerably more powerful, when applied correctly. It enables structure and consistency at scale by:

Used this way, AI reinforces the contracting model and enables it to operate consistently at scale.

Contracts: One Size Does Not Fit All

One of the most persistent inefficiencies in contracting is the failure to segment work appropriately. In most organisations:

• Majority of contracts are high-volume, low-risk agreements
• A small proportion are complex, high-risk negotiations

Yet many teams apply the same process to both. The result is that:

• Contracting processes slow down unnecessarily
• Senior lawyers are pulled into routine work
• Cycle times extend without adding meaningful value

AI does not need to solve the most complex contracting problems to deliver meaningful value.  In fact, this is often where it struggles.

Applied correctly with defined playbooks and human oversight, AI should already be supporting all of your high-volume routine contracting activity.

That is where substantial capacity is released.

Data: The Most Underutilised Asset in Legal

Contracts are one of the richest sources of commercial and risk data in any organisation. Yet in many businesses, that data remains locked in PDFs and spreadsheets, stored but rarely used. This represents a significant structural opportunity that many legal functions still fail to utilise.

AI changes this by making large-scale extraction and analysis commercially viable. It enables legal teams to answer the questions the business is actually asking:

• Where are we overexposed from a financial, compliance, or operational risk perspective?
• Which clauses consistently slow down deals?
• Where are positions repeatedly being conceded?
• How does contracting performance vary across regions, teams, and counterparties?

This level of insight allows legal teams to move beyond reactive support and operate more proactively as business advisors.

AI is a Multiplier, Not the Strategy

There is a risk in treating AI as the solution. AI will not fix a poorly designed contracting model. It amplifies the system already in place, whether that system is disciplined and scalable or fragmented and inconsistent. The real leverage comes when AI is applied within a disciplined operating model:

• Clear segmentation of contract types
• Defined playbooks and fallback positions
• Structured intake and triage processes
• Strong governance and human oversight

In that context, it acts as a multiplier:

• Review cycles compress
• Outcomes become more consistent
• Data becomes visible and actionable

Without that foundation and insight, AI becomes just another underutilised tool with organisations struggling to drive internal adoption.

Final Thoughts

Legal teams do not just need more tools. They need to think differently about contracting, and the starting point is not AI. It is recognising that contracting is not simply a workflow to be managed, but a strategic capability to be engineered.

Organisations that make that shift will not just move faster. They will improve risk control, reduce cycle times, lower operational costs, and provide greater visibility into contracting performance. Beyond those operational gains, they will position legal at the centre of how the business operates rather than at the end of the process.