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Now Assist genAI skill redesign

A flexible framework that allows for effortless management of 10 to over 1000 GenAI skills, including both custom and newly released options, while offering clear and contextual information to assist users in understanding each skill and making informed business choices.

Challenge

We currently offer an extensive library of over 1,000 Now Assist skills. However, this breadth of options has led to reduced visibility and complexity for both our internal business units and external customers.

As a result,

Users find it challenging to quickly identify, understand and utilize the most relevant skills, which hampers onboarding and prolongs the time-to-value for AI capabilities.
Product stakeholders regularly ask for performance insights once a GenAI skill is activated, but the difficulty of extracting meaningful metrics often leaves the team uncertain about its true value.
Customers who are in their early stages bring up up trust, accuracy and data privacy concerns.

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Key goals

Scalable by design: Seamlessly supports anywhere from 10 to 1,000+ standard or custom GenAI skills.
Effortless discovery: Smarter search and clear categorization surface the right skills in fewer clicks.
Instant access: One-click entry to each skill’s overview, activation, and management controls.
Rich context: Deep-dive pages outline prerequisites, metrics, and best practices to drive confident decisions.
Streamlined organization: Intuitive grouping and labeling keep the growing library easy to navigate.

Business impact

Faster roll out

Enables faster rollout of GenAI capabilities across the organization, reducing time-to-value and supporting broader adoption at scale.

Scalability

Provides flexibility to evolve with business needs, accelerating innovation by empowering teams to build and deploy tailored GenAI solutions efficiently.

Improved decisioN

Supports smarter business decisions and responsible AI use by surfacing context, dependencies, and expected outcomes of each skill.

Project timeline and team

Timeline: 4 weeks

Collaboration: 1 researcher, 2 product managers, PMs from the business units, 1 content writer, 4 engineers

Design approach

Internal research: Due to the limited time available, a quick turnaround was necessary. I began by addressing the initial issues raised by several internal product owners who were using this framework to develop their own GenAI solutions for. I organized interviews with our internal users, including admins and solution architects, in collaboration with our researcher.

Core team workshop: Additionally, I conducted a workshop with the core team (PM, engineers, QE, researcher, content writer) to align on expectations and goals. process allowed me to gain valuable insights and establish a solid understanding of the challenges from various perspectives.
Rapid prototyping and validation: I adopted a rapid prototyping approach to validate some of the initial assumptions.

Key takeaways

Positives

Easy to find skills, filters, search, sort, and actions; layout well liked
80% preferred the upfront “activate” button
New detailed view and layout favored
Pre-requisites and next-steps section viewed as a very helpful guide
Usage widgets valued for tracking performance
Notifications with deep links seen as very useful

Improvements

Filters: Include more filters and conditions as they may vary based on different types of skills
Upfront guided setup details: Provide clear upfront information about activation steps, especially for guided setups.

Activation button: As the primary action on the page, placing the activation button closer to the core content will help.
Similar skill section: Reassess the need for this section, as it might distract users.

ROI metric: An auto-calculated metric showing the value of the skill was the most requested.
Explainability: Adding explanations for each usage section, with the ability to drill down into specific details was requested.
Usage data consolidated and prioritized: 80% of participants preferred having all usage data in one area or widget before the next steps.

End-to-end designs

After consolidating all the findings and conducting a few more rapid iterations, I brought the team together to on the updated designs for the skill pages. These designs then underwent a more scoping process and a implementation approach.

Discover genAI skills

Users can browse diverse categories of the latest GenAI skills while an AI assistant narrows results to their context—ticket volume, active subscriptions, business goals—so they find the ideal match fast.

GenAI skill detail before activation

Explore each GenAI skill at a glance: see what it does, where it fits, required setup, real-time usage metrics, and one-click activation—everything you need to decide, enable, and manage with confidence.

GenAI skill detail after activation

After activation, the Skill detail view lets admins track adoption, accuracy, and real-time security alerts—making it easy to spot issues and fine-tune the GenAI skill over time.

Outcomes

The initial version is set to be released in July 2025. We are adopting a phased approach and actively collecting feedback from early users to enhance this experience further.