Icertis Connect, Boston, June 1–3, 2026

In early June of this year, the MGI analyst team attended Icertis Connect 2026 in Boston, MA. The event provided a window into how vendors like Icertis are navigating AI opportunities and risks and helped gauge user perceptions and buying and adoption intent with regard to CLM and Gen AI. Over 400 professionals attended the event with roughly half representing users from over 90 Icertis client organizations such as Eastman Chemical, Thermo Fisher Scientific, KPMG and Phillips 66 among others – a subset of the overall installed base.

Icertis made several product announcements at the event, but the most important takeaways from the conference were in both the depth and variety of largely unfiltered user presentations and comments made by Icertis users on the sidelines of the event. Icertis’s event team pointedly made no effort to “market-up” user presentations, opting instead to let clients speak freely and earning the company significant credibility points. The customer presentations were unvarnished and presented the full spectrum of the great, the good, the bad, and the ugly – company CLM origin stories, hard numbers, successes, implementation challenges and candid failure lessons without flash or fanfare. This approach is consistent with what we heard at Icertis Connect 2025 in NYC.

As a company, Icertis is navigating four transitions at once, and how it sequences them will determine whether customer trust converts into the next chapter of growth.

Four Simultaneous Transitions

Market

Legal and contracting work is shifting from people-plus-documents to AI-driven workflows. CLM demand keeps expanding at an above-average clip, but AI resets what buyers expect a “contract system” to do and who inside the enterprise sponsors it. Core CLM products are seeing increased competitive pressures from AI-native legal augmentation tools, from a growing number of CLM-light tools claiming an AI-native moniker and from vibe-coding attempts by some customers.

Leadership

Co-founder Samir Bodas, sole CEO from 2009, stepped down in August 2025 for health reasons and passed away in January 2026. Successor Anand Subbaraman keynoted Connect in June; six weeks later (July 17) the board announced his exit and installed CFO Rajat Bahri and board member Jim Moffatt (now Board Chair) as interim co-CEOs while a search firm seeks a permanent chief.

Capital

Icertis is a 17-year-old, late-stage private company with over half a billion dollars raised, last valued at ~$5B, with strategic holders including SAP and SoftBank. Investors of that vintage want a path to liquidity. A CFO/board-member interim pairing typically emphasizes financial discipline and keeps every strategic option – IPO, sale, recapitalization – on the table.

Product

The platform is being repositioned from CLM system of record to “AI-native contract intelligence”. This is more than a rebrand as it includes the launch of the new Vera product family and a new monetization model. All of this is landing in 2026.

Product Announcements at a Glance

  • Vera Engage: agent-driven drafting, redlining, and playbooks for pre-signature, multi-user work.
  • Reimagined Vera Copilot: natural language “ask pane” across the contract corpus; no upfront attribute configuration required. Positioned against generic GPT tools: no upload limits, contracts already in the system, grounded in company context.
  • Vera Analytics Advanced: portfolio-wide risk surfacing, clause harmonization, and prompt-driven extraction from unstructured contracts; to be included in the platform starting July. This marks a notable shift toward bundling AI into the base offering.
  • Vera Analyze: GA “next week” at event time; 50–100K documents/day throughput; four tools (portfolio analysis, insight search, AI-assisted prompt creation, guided analysis/portfolio builder). Gaps acknowledged: no connectivity to Engage yet, outside data requires API work, no download/share.
  • Vera Foundation: the underlying stack includes intent orchestration, hybrid RAG, low-latency retrieval, contract and knowledge graphs and a stated ambition for an “agentic control plane” to become the only UI needed for contracting work. Icertis claims ~60% of accounts now touch Vera.
  • SAP alliance: SAP’s intelligent contracting experience inside Ariba is powered by Icertis; Icertis fields a dedicated ~7-person SAP team, half of them 20-year SAP veterans. Word editing in that flow remains web-only and SAP, despite headlining the keynote, was not a listed sponsor.

What Customers Said: The Evidence Is the Story

  • A Canadian energy infrastructure company live with Icertis since 2018 shared the most instructive experience of the event. An early big-bang, attribute-heavy, single-tenant rollout made operating complexity “sky high.” The fix was subtraction: narrowing the aperture increased use and value, and ~1,000 provisioned users were deliberately scaled back to a focused base that four people now support across thousands of contracts. The payoff is real – when a VP in this regulated business needs a specific agreement, retrieval is four minutes (compared to weeks pre-Icertis). Its CLM vendor selection discipline is a template for others to emulate: the company started with capabilities rather than fast-moving features, screened ~20 vendors, and ran demos and POCs. Next up on its agenda: three projects to extract more from the investment, and a wish list of more – and more reliable – contract-analysis agents.
  • A US-based semiconductor equipment firm running SAP and Microsoft is on its third CLM – “people hated our last CLM” and consolidated 40K contracts onto just 18 templates in a global rollout spanning the US, Europe, and Asia. Result: 2x contract throughput, which was the goal, with ~2,500 users (~100 in legal), in-person training and refreshers, and a six-person support team. Its philosophy was the bluntest of the event: treat legal like a business; “not every contract is a creative writing exercise,” templatize and remove human touch from drudgery while keeping lawyers relevant; and pace the AI journey.  Going from SharePoint to AI-first overnight is no more realistic than running a marathon off the couch. Candid caveats: attorney adoption remains uneven, and “we still find contracts in drawers.”
  • A US-based chemical manufacturing company, live with Icertis for five years, spent two years cleaning data before value flowed and anchored the program in a CLM center of excellence housed in legal ops but explicitly serving IT, sales, and finance.
  • A Texas-based oil and gas energy provider has been live with Icertis for three years with 800 provisioned users, ~500 monthly active users, 100+ contract types on <300 templates, and 50%+ of contracts, buy- and sell-side is furthest along on AI in production analytics. The company is using prompt-driven extraction to answer questions like “which contracts mention AI usage policies,” yet Vera Copilot remains in its test environment.
  • A major tax, audit, and advisory firm based in the US has been a client since 2024, and has levered Icertis to execute 50–400 sell-side agreements daily and ~75K annually across tax, audit, and advisory. This company is six months in and validated the platform with 150 POC test cases before scaling.
  • A US bank compressed selection (September 2025) to an NDA go-live on June 2, 2026, using Icertis professional services – proof-positive a deliberately narrow first release can go live in months, not years.
  • Smaller organizations echoed the pattern: a US-based, international non-profit focused in healthcare research with under 100 employees described a troubled implementation that dedicated support ultimately fixed. Across nearly every interview, customer support was the most consistently praised element of the Icertis relationship, while over-configuration, cost, and near-term-only implementation design drew the most consistent criticism.

On AI, customer posture ranged from zero-tolerance policies to cautious piloting; nobody on the floor described autonomous contracting in production. The consensus metaphor from the customer panel: AI is an intern capable of doing a strong first pass, not an agent running a project end to end. Even self-described AI-first companies admitted they are immature internally. Tellingly, despite an AI-saturated agenda, audience questions overwhelmingly targeted core CLM basics: implementation best practices, adoption, data quality, and template governance. The synthesis across every successful implementation is the same: value comes from contraction, not expansion – fewer attributes, fewer templates, deliberate scope, clean data, configuration over customization, and trained, supported users. As the Canadian energy infrastructure company put it: “you aren’t centralizing a contract, you are digitizing it”. If lawyers can’t work in Word, they won’t work in your CLM.

Incongruities and Watch Items

Vision vs. floor demand

The vendor sold autonomy; the audience asked how to get lawyers to log in. The “agentic control plane as the only UI” collides with Word being legal’s love language. With roughly half of customer AI stories still running in test environments, alignment is still forthcoming.

Adoption arithmetic

Shrinking or flattening active-user counts within mature organizations are often healthy practices – but it caps Icertis’s seat-based expansion and makes AI monetization the growth engine by necessity. This trend appears just as Analytics Advanced moves into the bundled platform. Pricing power through this shift is the metric investors (and users) will be watching.

Transition stack-up

An AI-native rebrand, a bundling/monetization change, and an interim co-CEO structure are landing simultaneously at a late-stage company whose investors will soon press for liquidity. Icertis’s roadmap may see more flux until a permanent CEO is seated; buyers and current users would be well served staying close to multiple Icertis contacts.

Actions – User Best Practices

  • Start narrow and instrument adoption from day one (active users, cycle time, retrieval time).
  • Resist attribute sprawl (configuration over customization).
  • Fund comprehensive data cleanup before AI.
  • Avoid ambitious simultaneous legal transformation and CLM implementation.
  • Require in-production references for any Vera module.
  • Get roadmap, pricing, and support commitments in writing given the leadership transition.

Actions – What Icertis Can Do

  • The customer base handed Icertis leadership the playbook: productize the discipline observed by the Canadian energy infrastructure and US semiconductor equipment customers as packaged, documented implementation methodology and judiciously leverage the customer trust earned by the Icertis support organization.
  • Publish named, measured, in-production AI case studies; the “AI as an intern” framing is credible and sellable today, but full autonomy is not yet.
  • Give the market a clear leadership and ownership narrative quickly; enterprise buyers sign multi-year commitments with companies, not roadmaps. Users express high satisfaction with Icertis outcomes, while journey satisfaction is an evolving picture with room for improvement.

Bottom Line

Icertis remains the standard-setter for complex, regulated, global contracting, and its customer evidence base – candid, quantified, and loyal – is a genuine competitive asset, arguably stronger than its AI demos. As a company, Icertis is in the midst of a major evolution. The product portfolio, pricing and monetization approach, and internal leadership are all changing and maturing.  Like many of its peers, the company also faces investor desire for an outsized outcome.  The customers on stage showed CLM and AI value is derived from discipline and focused execution.  Icertis’s next-level AI and company ambitions will earn attention – and deliver shareholder rewards – if the company applies that same discipline to itself.