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Estd 4.22.2023
It’s an age-old problem in procurement: buyers don’t have time to negotiate fully with every supplier. Historically, one analysis found that around 20% of suppliers end up with unnegotiated “cookie-cutter” contracts – essentially money left on the table. Now, artificial intelligence is stepping in to close those gaps. AI-powered negotiation bots can autonomously engage suppliers, analyze data, and strike deals at scale. Instead of leaving smaller contracts on default terms, companies are using AI agents to secure better prices and conditions without adding headcount. In short, AI is poised to take over procurement negotiations – handling routine deal-making with unprecedented speed and precision.
How AI Is Changing the Game
Leading companies are already augmenting their procurement teams with AI, and the results are dramatic. Walmart, for example, deployed a negotiation chatbot to handle long-tail suppliers that were previously ignored due to cost constraints. In a pilot, Walmart’s AI negotiated deals with 64% of targeted tail suppliers in just 11 days on average. The bot secured roughly 1.5% in cost savings and extended payment terms to 35 days on those contracts. Each side gained something of value, proving the AI could create win-win deals at scale. Walmart has since expanded the chatbot to more categories (even mid-tier suppliers) and into multilingual negotiations.
Sanofi (a global pharmaceutical firm) similarly transformed its sourcing. By applying AI-driven should-cost models and running digital negotiations, Sanofi achieved an average 10% reduction in spend and boosted negotiation savings by 281%. Another enterprise, BT Group, embedded generative AI in its sourcing platform to drive double-digit cost savings across billions in annual spend. These real-world wins underscore AI’s practical value: more deals closed, better pricing, and tangible bottom-line impact.
Even suppliers are embracing the new normal. Many vendors report positive experiences negotiating with AI assistants. In one deployment, 90% of suppliers said an AI-led negotiation was as easy or easier than a human-led one. The takeaway is clear: AI negotiators aren’t just fast – they can be fair and even preferred by suppliers when both parties benefit.
From Sourcing to Supplier Management: End-to-End Automation
AI’s influence extends beyond bargaining over price. Modern agentic AI systems can automate sourcing events, contract management, and ongoing supplier oversight. Advanced procurement platforms use generative AI to draft RFPs and contracts, synthesize market data, and even recommend negotiation tactics. For instance, AI category management tools can quickly scour thousands of data points to find qualified suppliers. They also predict optimal sourcing strategies in a fraction of the time it once took. In negotiations, AI co-pilots craft scripts and play out counterargument scenarios to pressure-test strategies. The latest models can even role-play both buyer and seller in simulation, then suggest which approach (collaborative, confrontational, etc.) is most likely to succeed.
On the execution side, autonomous negotiation agents (like Walmart’s chatbot or specialized AI platforms) can handle thousands of supplier discussions in parallel. These AI agents follow predefined objectives (e.g. target discounts or extended payment terms). They iterate with suppliers via chat or email until reaching an agreement or impasse. All the while, they reference internal data (spend history, should-cost benchmarks) and external market rates to negotiate fact-based deals. McKinsey notes that AI can execute such analysis ~90% faster than traditional methods. In practice, that means procurement teams can address far more contracts and unlock up to 2× more value opportunities that would have been missed.
AI also brings continuous vigilance to supplier management. Machine learning models monitor supplier performance and flag risks early. A system might automatically calculate should-cost benchmarks for thousands of items, arming buyers with data for robust, fact-based negotiations. Gen AI tools compile risk intelligence by mining news and social media for red flags. They can even auto-draft routine communications like performance reports, escalation emails, or contract clauses. By taking over tedious tasks in sourcing, negotiation, and vendor monitoring, AI frees human professionals to focus on strategy, relationships, and innovation. As BCG observes, early adopters can run leaner procurement teams and devote more time to strategic work. Meanwhile, AI handles the grunt work in the background.
Some examples
1. SAP Ariba (Procurement Network and Suite)
SAP Ariba provides sourcing, procurement, and supplier network tools and is known for its unique monetization via network fees. Enterprises license Ariba’s software (e.g. for e-sourcing, contracts, or procure-to-pay) on a subscription basis (with recent median pricing around $73k/year for mid-sized enterprises). In addition, Ariba monetizes the SAP Business Network: suppliers transacting with buyers on Ariba may incur fees based on volume.
Pricing Model: Ariba’s SaaS fees for buyers are typically subscription-based (often negotiated per module or enterprise size), while suppliers pay transaction fees of about 0.155% – 0.35% of the transaction volume on the network (capped at $20k per supplier per year). This dual model means the platform captures value from high transaction throughput. Ariba has been adding AI features (like guided buying and invoice anomaly detection), but its monetization remains tied to software licenses and network usage rather than discrete AI add-ons.
2. Arkestro (Predictive Procurement)
Arkestro is an AI-driven sourcing and RFQ automation platform (formerly Bid Ops) that acts as a “predictive procurement orchestration” tool. It uses machine learning and behavioral science to recommend optimal suppliers and target prices during sourcing events. Arkestro can autonomously suggest awards or negotiate bids to achieve savings in tactical sourcing. Real-world use shows Arkestro’s algorithms delivering ~18–19% cost savings on average for each $1M of spend.
Pricing Model: Arkestro is offered as enterprise SaaS – likely an annual platform fee – rather than per seat (procurement teams are small). The pricing often correlates with spend under management or number of sourcing events. For example, a license might cover a certain spend volume through the system, aligning cost with value delivered. While Arkestro’s website doesn’t publish prices (custom quotes are the norm), its value proposition and case studies (18.8% savings per $1M) imply the ROI is high. Pricing is thus outcome-driven; clients pay for the platform with the expectation that savings vastly exceed fees (a value-based approach common to “AI procurement” tools).
4. Fairmarkit (Tail-Spend Sourcing Automation)
Fairmarkit focuses on automating low-value (“tail spend”) purchases. It uses AI to identify the best-fit suppliers and automatically conduct RFQs/RFPs for purchases that procurement staff often overlook. This system intelligently invites suppliers, collects bids, and can even handle autonomous negotiations for routine buys. Companies like Boeing, BP, and Snowflake use Fairmarkit to source thousands of small purchases. The platform touts significant efficiency and cost benefits – e.g. reducing manual sourcing time to 3 minutes per event and achieving over 90% of bids below benchmark pricing.
Pricing Model: Fairmarkit is provided as a B2B SaaS solution, usually as an annual subscription to the platform. Pricing is typically tiered by usage – for instance, by the number of RFQs managed or total tail-spend dollars automated – rather than by user count. Large enterprises might pay a flat fee covering a volume of events (ensuring each buyer enabled on Fairmarkit can drive ~$40k savings per week on average). In practice, Fairmarkit often integrates with procurement suites (it’s Coupa-certified) and is sold on its demonstrated ROI in cost savings and productivity, justifying its subscription cost by automating labor-intensive processes at scale.
4. Pactum (Autonomous Negotiation Bot)
Pactum is a conversational AI platform that negotiates with suppliers or vendors automatically via chat. In procurement, Pactum is deployed to handle high-volume, low-value negotiations that procurement teams don’t have time for – for instance, renegotiating payment terms or bulk discounts with long-tail suppliers. The AI agent conducts multi-round negotiations within preset guardrails. Real-World Example: Walmart uses Pactum’s chatbot to negotiate with thousands of its smaller suppliers simultaneously. Results have been impressive – 68% of suppliers approached reached agreements with the AI, with an average 3% savings achieved in those deals. Notably, 75% of those suppliers actually preferred negotiating with the bot over a human, due to its quick, data-driven haggling. Pactum enabled Walmart to finalize deals in days (vs. weeks) and freed up human buyers to focus on strategic contracts.
Pricing Model: Pactum’s model exemplifies outcome-aligned pricing. While specifics are usually custom, many engagements are structured with performance-based fees – e.g. a portion of the savings achieved or a success fee for each deal closed. This makes sense: Pactum literally delivers quantifiable dollar savings (by securing better terms), so the vendor often shares in the value. Contracts often start with a setup fee and a base subscription for the AI service, then a “gain-share” component where, say, 10-15% of the negotiated savings are paid as fees. This aligns incentives and means the cost scales with results. (For instance, if Pactum’s bot saves $10M for a company, the fee might be a few percent of that.) This model is outcome-driven and low-risk for clients. Pactum’s growing roster of $5B+ companies like Maersk and Wesco indicates that enterprises are willing to pay via savings-based models. In sum, Pactum monetizes by automating thousands of micro-negotiations and taking a slice of the improved margin it generates, alongside any fixed platform fees.
5. Coupa (Business Spend Management Suite)
Coupa is a leading B2B SaaS platform that covers procurement, invoicing, expenses, and spend analytics. It embeds AI in features like spend classification and community intelligence (benchmarking prices using aggregated data). Enterprises use Coupa across the procurement lifecycle – from sourcing events to purchase orders and analytics.
Pricing Model: Coupa is sold as a modular enterprise subscription (not per transaction). Customers typically buy annual licenses for selected modules (procurement, invoicing, sourcing, etc.), often tiered by company size or spend volume. For example, recent deal data shows a wide range (around $22k to $208k per year) with a median annual spend of about $90k for the platform. This suggests most enterprises pay six-figure subscriptions for Coupa, scaling with modules and usage. Coupa’s model is primarily per-module or outcome-based (savings/visibility), rather than per-seat – aiming to cover 100% of spend under management for the client.
Trend Forecast: Autonomous Procurement on the Rise
The trajectory is unmistakable: procurement is marching toward autonomy, guided by AI. Industry analysts project major growth in AI-driven negotiations in the next few years. For example:
- By 2027, 40% of all sourcing events and 50% of supplier contract negotiations will be handled by AI-powered systems. In other words, a big share of vendor selection and deal-making will run on autopilot with minimal human intervention.
- By 2029, 80% of routine procurement decisions will be augmented by generative AI. These AI advisors won’t replace human judgment, but they’ll provide data-driven insights and options so procurement managers can make smarter final calls.
While some fear AI replacing jobs, the reality is more nuanced. Procurement roles will evolve, not vanish. AI will take over repetitive paperwork, data crunching, and basic negotiations – but humans will still lead complex strategic deals and supplier relationships. Gartner emphasizes that as AI handles communication-heavy tasks, human creativity and expertise become even more valuable for solving novel problems. In practice, tomorrow’s procurement teams might be smaller but more specialized. They’ll focus on critical thinking, supplier development, and strategic planning, with AI as a trusty co-pilot for everything else.
Forward-thinking companies are already adapting to this future. They are upskilling staff in data and AI, and redesigning processes to integrate virtual buying assistants and analytics. Organizations that don’t embrace these tools risk falling behind. Simply put, autonomous sourcing and negotiation isn’t a far-off vision – it’s happening now, and businesses must adjust to stay competitive.
Implications for SaaS Pricing Strategy in an AI-Driven World
What do these procurement–AI trends mean for SaaS companies, especially those selling to enterprises? In short, SaaS pricing strategies must get smarter and more flexible. If buyers are using AI to benchmark your pricing and even deploy bots to negotiate, your pricing model must hold up under scrutiny. Enterprise software vendors may encounter AI-enabled procurement agents pushing for usage-based contracts or outcome-based deals. SaaS providers should be ready to justify their SaaS pricing models with solid ROI data, as AI will quickly flag any misalignment between your price and the value delivered.
For SaaS companies building AI-driven procurement tools themselves (or any AI that automates sourcing tasks), pricing strategy is even more critical. Traditional seat-based licensing may not make sense when an AI agent – not a human user – is doing the work. Across these examples, we see a spectrum of monetization strategies for AI procurement tools:
- Usage-based pricing – charge based on consumption (data processed, number of negotiations, etc.). This aligns price with actual use. Some experts predict AI software will be priced more like cloud services or databases – essentially charging for compute or transactions.
- Outcome-based pricing – tie fees to results, such as a percentage of cost savings achieved or other KPIs. If an AI negotiation agent saves a customer $1M, the provider might take a small success fee. Pactum’s success-fee model both exemplify pricing that tracks outcomes (savings achieved, efficiency gained). This aligns the AI vendor’s revenue with the financial benefits delivered, which resonates well in procurement where cost savings are measurable.
- Hybrid Models – Many enterprise deals blend these approaches. For example, a client might pay a base subscription plus a performance kicker. Or license a platform broadly but with limits/tiers that correspond to usage (as with Ariba’s tiered supplier accounts).
The common thread is that pricing should reflect AI’s added value without alienating customers. Tech investor Tom Tunguz argues that AI products offering outsized productivity could justify premium pricing. For example, if an AI performs the work of three employees, a vendor might ultimately charge roughly three times a typical single-license fee. Of course, any shift from familiar models requires careful change management. SaaS pricing consultants often recommend hybrid structures – say, a base subscription plus a variable usage or performance-based component. This ensures a baseline revenue while sharing upside with customers. Above all, be prepared for more frequent price reviews and data-driven negotiations. In an AI-driven procurement era, a well-crafted pricing strategy becomes a competitive advantage for SaaS firms.
Embrace the Future with a Strategic Edge
AI is no longer just a buzzword in procurement – it’s a practical tool delivering faster deals, smarter decisions, and significant cost savings. Forward-looking procurement teams are leveraging AI to negotiate better contracts and streamline supplier management. For SaaS businesses, adapting to this new reality is crucial. Those who align their pricing, product packaging, and value messaging with an AI-powered future will win more deals and deepen customer trust.
Monetizely can help you stay ahead. As pricing strategy experts, we’ve seen how AI is reshaping B2B sales and procurement. Our team ensures your SaaS pricing strategy stays competitive in the age of AI. That could mean transitioning to usage-based models, defining new value metrics, or repricing your AI-driven features. Contact Monetizely for a free pricing audit tailored to AI-driven SaaS companies. We’ll help you identify quick wins and long-term changes. Our goal is to maximize revenue in this new era – where AI and pricing strategy go hand in hand.