Turn AI Signals Into Trusted Next Best Actions
Combine real-time signals, business rules, and explainable recommendations so teams act on what matters most with greater speed and consistency.
Key AI-Enabled Recommendation Challenges
Recommendations create value when teams trust both the signal and the logic behind the next move. That’s when leaders start asking decision questions like:
Are we...
…clear on which decisions need recommendations most?
…helping teams trust the signal and logic?
…explaining why this action should surface now?
…prioritizing recommendations by value and capacity?
…using feedback to improve recommendations over time?
The Bottom-Line
Recommendations create value when they surface the right next action with clear logic, timing, and feedback.
Build the recommendations engine teams can trust to act on
Our AI-Enabled Recommendations Engine Playbook helps leaders turn fragmented signals, business context, and decision logic into trusted next best actions—so teams can prioritize faster, act more consistently, and improve outcomes across high-value workflows.
Recommendations Engine
Launch Pad
Launch Pad
Weeks 1 - 4
Baseline Your Readiness
Develop a clear measure of your current state readiness including:
- Structured 1:1 discovery sessions to clarify where recommendation quality, explainability, and actionability are breaking down
- A targeted readiness scan to pinpoint the highest-impact gaps across signals, decision logic, governance, and adoption
- An executive brief covering AI-enabled recommendation best practices, scaling implications, and priority actions
2 Hr. Leadership Alignment & Action Planning Session
A high-impact leadership working session focused on:
- Clarifying where next-best-action recommendations can create the most value across customer, operational, and risk-sensitive workflows
- Exploring applied Use Cases, adoption best practices, and key “Watch Outs”
- Aligning on an actionable scaling plan
Recommendations Engine
Mission Control & Lift-Off
Mission Control & Lift-Off
Weeks 5- 12
Benchmark Assessment + Acceleration Guides
Develop a clear view of your AI-Enabled Recommendations Engine capability, including:
- Identifying and prioritizing the gaps most likely to limit recommendation quality, trust, and actionability
- Exploring our 20 AI-Enabled Recommendations Engine Acceleration Guides for targeted recommendations and resources
- Leveraging a GenAI Strategist-led planning session to define your action plan
Deep Dive Practitioner Certification Series
Explore core concepts & methods in our AI-Enabled Recommendations Engine certification series, including:
- Designing High-Value Recommendation Use Cases
- Signal Integration, Feature Readiness & Decision Context
- Next-Best-Action Logic, Explainability & Prioritization
- Governance, Controls & Closed-Loop Learning
- Measuring Recommendation Impact & Continuous Improvement
- Co-deliver quick wins to “make it stick” and accelerate your target state delivery goals
Recommendations Engine
Mission Accelerate
Mission Accelerate
Weeks 12+
Scaling Play Book Design & Implementation
Configure and operationalize your scaling approach, including:
- Configuring and customizing your AI-Enabled Recommendations Engine scaling playbook
- Operationalizing your AI-Enabled Recommendations Engine Target Operating Model (TOM) across decision points, roles, and workflows
- Optimizing and evolving your TOM as signals, priorities, and business needs change
Insights Design & Implementation Support
Turn data into insights and insights into action by:
- Configuring and customizing your AI-Enabled Recommendations Engine metrics and insights plan
- Operationalizing your AI-Enabled Recommendations Engine Insights Plan and supporting operational processes
- Optimizing and evolving your insights to improve recommendation quality, adoption, and business impact
Weekly Quick Wins
An actionable set of applied Quick Wins to build and sustain momentum, structured as:
- < 30 Days Wins: Lightly configurable resources and solutions
- 30 – 60 Day Wins: Lightly customizable Quick Wins
- 60 – 90 Day Wins: Increasingly high value Quick Win deliverables
Your Acceleration Plan
- Baseline where recommendations add value, where signals are weak, and where decision logic breaks down
- Tailor the plan to the decisions, signal gaps, and prioritization logic that most affects action
- Deliver Quick Wins, build capability, and scale priority solutions through one integrated plan
Your Comms Plan
- Identify your priority stakeholders, communication needs, and recommendation adoption gaps
- Configure and deliver a tailored AI-Enabled Recommendations Engine communications plan, custom Comms Hub, and role-specific enablement assets
- Build and sustain momentum with explainers, demos, videos, and proof points.
Your Change Plan
- Define your quarterly AI-Enabled Recommendations Engine review, optimization, and adaptation process
- Enable quarterly strategy and scaling plan updates, with rapid response to major market, customer, operational, and competitor shifts
- Keep your AI-Enabled Recommendations Engine approach evergreen by continuously improving how recommendations are generated, prioritized, and translated into owned action
On-Demand Coaching
- Identify where your teams need targeted coaching to overcome recommendation design, prioritization, or execution gaps
- Deliver tailored expert support, working sessions, and practical guidance
- Help your teams strengthen AI-enabled recommendations, improve actionability, and keep your Recommendations Engine efforts moving forward
Choose Your On-Ramp...
Choose the starting point that fits your recommendations engine urgency, maturity, and scope—from focused alignment to quick wins or a full playbook.
An Accelerated Alignment & Action Planning Sprint
A fast-paced leadership alignment and action planning sprint to:
- Baseline your current recommendations engine maturity
- Explore recommendation best practices
- Align on top priorities
- Define your path forward
- Identify near-term Quick Wins
Accelerate & De-Risk Your AI-Enabled Recommendations Engine Journey
Confidently scale your AI-Enabled Recommendations Engine with a tailored TOM that helps you turn AI signals into trusted next best actions at scale.
Targeted AI-Enabled Recommendations Engine Solutions
Rapidly solve targeted AI-Enabled Recommendations Engine scaling challenges, including:
- Baseline your current recommendation and actionability gaps
- Solve a high-priority recommendations challenge
- Clarify your target decision-support priorities
- Align on practical actions to move forward
- Deliver focused progress in a matter of weeks
We needed more than another dashboard. This helped us define the right recommendation moments, connect them to business value, and give teams confidence in the next best action.
VP, Customer Experience, National Retailer.
Outcomes you can expect
Insights
Turn data, signals, and patterns into clearer recommendations about what to do next.
Actionability
Translate recommendations into clearer next best actions that teams can evaluate and act on more easily.
Confidence
Build greater trust that recommendations are useful, well-grounded, and worth acting on.
Efficiency
Reduce the time and effort it takes to decide what to do next by surfacing more targeted, timely guidance.
Impact
Translate stronger recommendations into better decisions, faster action, and more meaningful business results.
Complimentary Resources
Curious About What “Great Looks Like”?
Review our “AI-Enabled Recommendations Engine” Whitepaper
Want to See How You Compare?
Complete our AI-Enabled Recommendations Engine Scan or Assessment
Want an easy way to come up to speed?
Click here to listen to our AI-Enabled Recommendations Engine Podcast
Want to dig deeper?
Click here to check out our library of YouTube videos
Frequently Asked Questions
1. Why do this now?
2. What will we get?
3. Will it work here?
4. How do we make it real?
5. How do we make it stick?
- Why do we need an AI-Enabled Recommendations Engine now?
Because signals alone don’t drive action—leaders need sharper guidance on what to do next and where to focus. - What outcomes should we expect from this work?
Actionable insight, faster decisions, sharper prioritization, and stronger follow-through. - What happens if we don’t build an AI-Enabled Recommendations Engine?
Teams see the signals but still struggle to decide what matters most or how to respond.
- What do you mean by an “AI-Enabled Recommendations Engine”?
A capability that turns signals and context into next-best-action recommendations. - What are the main deliverables from this work?
Recommendation priorities, stronger decision logic, and a path to action. - What do “Quick Wins” look like in AI-Enabled Recommendations Engine work?
Target high-value moments, improve action logic, and move from signals to decisions faster.
- Does this only apply to highly mature analytics environments?
No—it helps wherever teams have enough signal to benefit from sharper next-step guidance. - Can this work across different teams and use cases?
Yes—it supports leaders, operators, and product teams across decisions and workflows. - Does this cover more than reporting and alerts?
Yes—it interprets patterns, prioritizes responses, and recommends actions—not just reporting and alerts.
- How do you decide where recommendations should be applied first?
We start where recommendations can most improve decisions, speed, and next-best actions. - How do you keep recommendations from becoming noisy or unhelpful?
We focus on the recommendation moments that matter most and keep guidance grounded. - How do you connect recommendations to business impact?
We tie recommendations to the decisions and follow-through that create stronger outcomes.
- Who should be involved from our side?
Business, product, technology, and analytics leaders who own the engine’s signals and decisions. - How do you keep the recommendations relevant as priorities change?
We define a recommendation model that evolves with signals, needs, and priorities. - How do you sustain this after the initial work is done?
We build a recommendation foundation that keeps improving actionability, confidence, and impact.
Turn AI Signals Into Trusted Next Best Actions
