Summary: With AI’s rapid advancements, product strategy must take a new approach. Adding AI bolt-on features won’t cut it. AI should be integrated intelligently to support tasks and enhance, not clutter, user experiences. This starts with how we approach UX strategy to support task-oriented AI-enhanced experiences.

The Need for a New AI UX Approach

Rethinking product strategy with AI involves more than bolting on AI features. Unfortunately, in the rush to get AI out the door, we’ve seen a lot of this in products: (an AI as a feature, mildly useful, mostly not)

Instead: AI UX strategy requires integrating AI to support tasks and enhance user experiences sensibly. By focusing on generative AI’s “fetch, synthesize, create” model, we can re-think how we create task flows and user interactions.

Why this Matters: Many teams view AI as a value-added component, limiting its potential. This approach results in reactive, feature-focused products. Instead, anticipating tasks, contexts and workfload triggers can help your AI UX be more proactive. It can also move you into the next wave of productivity AI.

Shaping User Expectations

AI is changing what users expect from products. Here’s how we can use AI to shape tasks and meet these new expectations:

1. Proactive Assistance: Design AI that anticipates user needs. For instance, an AI calendar app could suggest meeting times based on participants’ availability, streamlining scheduling.
2. Context-Aware Functionality: AI should understand user context to provide relevant support. For example, AI-augmented interfaces, sensors, or analysis of your situation can shape the next steps to meet the context. See Designing Context-Aware experiences
3. Continuous Learning: Implement AI that learns from user behavior and improves over time. This can be seen in recommendation systems that refine suggestions based on user preferences.

Task-Supported AI: The Right Approach

AI should empower users by handling repetitive tasks and enhancing their capabilities. Here’s how we can integrate AI to support tasks:

1. Fetch: AI can automate data retrieval, saving users time. For example, an AI-powered search engine can fetch relevant information based on user queries/ filters/ preferences, delivering useful results more quickly.
2. Synthesize: AI can process and combine data from multiple sources, providing users comprehensive insights. This can be seen in AI tools that analyze market trends and offer synthesized views or ad-hoc reports.
3. Create: AI can assist in creating content or meaning from data. Today, we enjoy generative AI drafting emails, generating ideas, or analyzing complex data sets. This heavy-lifting aspect is core, but decision-support for users is the sweet spot.

Key Points: The key to rethinking product strategy with AI is first to blend a task-oriented design approach with how generative AI approaches task completion. Next we can better align UX strategy toward Human-AI enhanced user interaction (see Microsoft guidelines). This prepares us to design better UX with AI and ensures that agents and ‘large action models’ (LAMs) build human-centered approaches.

Go deeper: Attend Frank Spillers Miniclass webinar Rethinking Product Strategy with AI

Topics Covered:

1. Redefining AI Product Strategy and UX:
   • How to build AI into your core strategy.
2. Proactive vs. Reactive AI Design:
   • Create AI that anticipates user needs.
3. Preparing for Large Action Models (LAMs) and Agent-Driven UX:
   • Future-proof your design process for advanced AI.

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