This year, three themes emerged from the 150+ payer executives, provider leaders, policy influencers, and risk-bearing innovators who attended Summit and are navigating the realities of risk contracting every day:
Despite meaningful progress in VBC adoption, many organizations still face the same operational barriers to interpreting results on a one-year cycle. Delayed performance data, misaligned contract measures, and time-consuming operational processes all hinder that ability. But leaders are adamant that value-based care is making a long-term impact, even if the most sophisticated organizations acknowledge that the mechanics of forecasting, risk adjustment, and contract settlement still struggle to keep pace with the ambition of their value-based strategies.
Most organizations are still operating within information cycles that were designed for fee-for-service healthcare: quarterly refreshes; lagged claims data; and retrospective reporting. When contracts include downside risk, that timeline simply doesn’t work.
Where ROI Actually Shows Up In VBC Panel
Participants in the panel on What it Takes to Win in Specialty Care constructed a four-step formula for success:
What it Takes to Win in Specialty Care Panel
All agreed that the first step to any successful VBC strategy was scoring the value of clinical interventions using actuarial rules and logic, prior to launching any initiative to ensure that financial goals are clear from the very beginning.
Our actuaries have scored various successful care pathways and interventions and trained Merlin AI to predict the unique contract value of using each of these insights. Financial leaders are already watching financial trends and asking Merlin to:
By using these interventions, clients are scaling these positive outcomes across providers, geographies and patient populations.
Healthcare leaders are no longer asking whether AI will play a role at the point of care, they are asking whether it is actually reducing costs or adding to them.
Across the industry, organizations are investing heavily in AI applications for clinical copilots, documentation, automation, coding assistants, and patient engagement tools. Many are also building internal AI capabilities, standing up data science teams and experimenting with proprietary models.
These efforts may ultimately yield clinical or operational benefits. But in the near term, leaders shared that they often introduce significant new costs: infrastructure investments, integration challenges, staffing requirements and opportunity costs; not to mention the ongoing model maintenance cost.
We believe that AI applications should reduce operational stress, even before they prove their value in any specific use case.
Summit attendees interacting with Merlin AI
As we move toward regular use of AI, industry executives warned us to be mindful of any data biases that train AI systems. It is not enough for AI to offer information for quick decision making; these systems must also be 100% transparent in showing their work – providing the data sets and logic used.
This is precisely what has been lacking in large AI systems.
In order for users to actually trust the financial advice of our Actuarial AI assistant Merlin, the platform was built to be responsible and explainable. Merlin keeps humans in the loop. Every answer is traceable, transparent, and customizable for each organization. Every insight is backed by Arbital’s validated actuarial logic, ensuring accountability and auditability.
When models are grounded in actuarial discipline (such as credibility theory, loss ratio modeling, risk adjustment mechanics, and regulatory standards) they can dramatically increase actuarial capacity while maintaining the transparency required for financial governance.
Trust remains the currency of risk contracting. Any system that informs financial decisions must operate within that framework of trust.
Highlighting Merlin AI at the Arbital Health Summit 2026
Leaders are excited about the next phase of VBC, both from a policy perspective and from an operational perspective. Organizations that succeed will leverage AI for immediate efficiency and speed of decision making, while requiring transparency and auditability.
The next phase of VBC will be defined not just by risk contracts, but by the intelligence infrastructure that supports them.
In VBC, timing matters. And increasingly, the difference between reacting to risk and proactively managing it comes down to how quickly leaders can see what is happening, so they can act with urgency.
The Arbital Health Summit Team