Peer to Peer: ILTA's Quarterly Magazine
Issue link: https://epubs.iltanet.org/i/1544492
P E E R T O P E E R M A G A Z I N E ยท S P R I N G 2 0 2 6 51 That steady improvement, backed by leadership support and the people who translate user needs and messy data into reliable workflows, is what separates firms that merely deploy AI from those that scale it into a durable capability. MATURITY AS A TRAJECTORY, NOT A DESTINATION The progression from chatbot to multi-capability assistant to expertise-grounded platform is not a three-step process with a finish line. It is a trajectory, one that accelerates when unified AI is paired with trusted, curated internal data and governed by disciplined feedback loops that steadily improve relevance, accuracy, and user confidence. As William Gaus, Chief Knowledge Management and Innovation Officer, explains, "Creating space for innovation starts with how you work with your teams. We've been intentional about building a culture where research and development is part of the job, not something done in the margins. That means giving people room to experiment, encouraging ideas to incubate, and treating early projects as learning opportunities rather than finished products. Over time, that collaborative, iterative approach is what allows meaningful capabilities like Athena to take shape and evolve across the firm." That mindset has been essential to Athena's progression. By allowing ideas to mature through collaboration and real-world use, the firm created the conditions for experimentation to turn into durable capability. The result is not just faster delivery of new features, but a platform that reflects how attorneys and staff actually work and continues to evolve alongside them. This becomes most visible in capabilities like expertise finding, where trust is earned only through consistent, grounded answers. Our firm's five-year head start did not just give us an early product. It gave us an early understanding of what maturity actually requires: security-first infrastructure, a willingness to experiment and sometimes fail, relentless attention to data quality, and a culture that treats AI not as a novelty, but as a capability to be refined. Firms that invest in reliability, data governance, and continuous improvement will pull ahead. Not because they moved fastest, but because they built something their people return to and rely on.