Unlocking GenAI’s potential with Now Assist
Now Assist isn’t a standalone product. It’s an intelligence layer woven across the ServiceNow platform, designed to lift productivity, sharpen decision-making, and push self-service capabilities well beyond what rule-based automation could ever achieve.
Brillio has spent years augmenting ServiceNow capabilities for clients through multi-platform, cross-functional workflows. That experience makes a difference when implementing Now Assist, because the hardest part isn’t the technology, it’s knowing which use cases justify the investment and which ones don’t. Two tracks define most Now Assist engagements. ITX transformation focuses on modernizing ITSM and extending service management principles across the organization through ESM and Pulse consulting. Hyper-automation, the second track, covers GenAI-led XaaS transformation, creator workflows, and the use of advanced analytics to find and size automation opportunities. Both tracks begin with an honest assessment of where an enterprise actually sits on the AI maturity curve.
Now Assist explained
Getting value from Now Assist starts with getting the assessment right. Brillio works with enterprises to evaluate current processes, identify where AI-driven automation adds the most value, and structure a rollout that doesn’t outpace the organization’s readiness.
In practice, Now Assist addresses process inefficiencies by automating routine tasks, cutting manual intervention, accelerating operations, and freeing employees for higher-order work. Real-time, contextual recommendations mean people get the right information at the right moment rather than searching across systems. Proactive issue management is another distinct capability: Now Assist can flag potential problems before they escalate, keeping services running without the reactive scramble that burns time and trust. On top of that, natural language processing makes interactions intuitive, and automated processes reduce the risk of human error in ways that manual reviews simply can’t replicate at scale.
Now LLMs or bring your own LLM?
One decision every enterprise faces is which AI models to run inside ServiceNow. Now Assist offers domain-specific Now LLMs, contextually optimized for ServiceNow code, content, and platform architecture. These models simplify complex data into plain-language summaries, surface insights from the broader ServiceNow customer base, and suggest next steps without requiring users to know what they’re looking for.
But the platform also supports a Bring Your Own LLM approach, letting businesses integrate models from OpenAI, Google Cloud, Azure OpenAI, or others directly into the Now Assist experience. This flexibility matters. An enterprise with significant investment in a particular AI stack shouldn’t be forced to abandon it at the platform boundary. The right answer depends on what the business already has, what it’s trying to accomplish, and how much customization the use case requires. Brillio helps clients navigate that choice with a clear-eyed assessment rather than a vendor preference.
How fast do organizations see results – and why maturity level matters
The core principle is straightforward: maximize the value of what enterprises have already built. That means avoiding the trap of over-engineering, creating technology archetypes that become obsolete before they pay off. Instead, we focus on clients’ existing platforms and infrastructure, identifying where combinations like Now Assist plus Copilot or Now Assist plus Einstein create a genuinely cohesive solution rather than another integration to maintain.
The classical approach of consolidating everything into a centralized data lake is increasingly difficult to justify. The ROI from that level of aggregation rarely matches the cost and complexity. Platform orchestration needs to be more dynamic, ServiceNow can stay in its own lane while use-case-specific APIs interact, execute, and return results without generating centralized tech debt. Mature organizations typically see measurable productivity gains within three to four months of a well-scoped AI implementation. Less mature organizations may need six months or more, but with the right maturity framework in place from the start, that timeline compresses.
Grooming a mature Center of Excellence and Innovation to drive GenAI imperatives
A Center of Excellence isn’t a committee. Done right, it’s the organizational infrastructure that makes AI adoption self-sustaining rather than dependent on a single implementation partner or internal champion.
Brillio helps clients build and mature their CoEI through three distinct structural models. A centralized CoEI runs integrated strategies across lines of business from a global function. A hybrid model blends global direction with local execution. A decentralized model empowers local teams to create customized workflows within a shared governance framework. The right structure depends on how the enterprise is organized, how its business units vary, and how much standardization is actually achievable across them. Whichever model fits, the CoEI is responsible for setting best-practice standards, managing the demand-to-release cycle, tracking KPIs, and ensuring that AI solutions are built to scale, not just to demo.
AI adoption frameworks and enterprise maturity levels
Brillio’s Pulse methodology structures AI adoption across four maturity levels, each with a distinct objective and set of activities. At the cognizance stage, the work is about creating genuine awareness, hackathons, interactive sessions, and webinars that make the benefits of AI concrete rather than abstract. At the tactical stage, cohort-based proof-of-concept programs target specific business units, building awareness and buy-in where it matters most.
At the strategic level, those cohort POCs scale into broader platform democratization, with resources generating new utilities on top of existing infrastructure. And at the transformational stage, AI is embedded into the core business and strategic plan across different business units, no longer a project, but a capability. The Pulse Framework also includes a ServiceNow Maturity assessment using a digital index, rapid value unlocking through cost and business impact analysis, and an ROI calculator that quantifies the transformation ServiceNow can deliver. This isn’t a theoretical framework. It’s the scaffolding Brillio uses to move clients from aspiration to accountability.
Revolutionizing a wide range of industries
Now Assist’s impact isn’t confined to a single vertical. In healthcare and life sciences, GenAI capabilities can assist in drug discovery, personalized medicine, and predictive diagnostics by identifying patterns across vast medical datasets. In banking and finance, fraud detection, risk management, and customer service automation are the near-term value plays. Retail benefits from personalized shopping experiences, smarter inventory management, and AI-driven customer service.
Manufacturing organizations are applying GenAI to supply chain optimization, predictive maintenance, and quality control. Media and entertainment companies use it for content generation and recommendation personalization. Education, the public sector, and high-tech industries each have their own high-value use cases, from intelligent tutoring systems to cybersecurity to accelerated software development. The common thread is that the enterprises seeing the most value aren’t waiting for a perfect strategy. They’re identifying the two or three use cases where Now Assist can make an immediate, measurable difference, and building from there.
