PUBLISHED DATE: 2026-06-05 04:00:43
STOP PILOTING.
START PROVING
The 90-Day AI ROI Plan
You Can Actually Use
FOREWORD
Off the back of PIMFA and Publicis Sapient’s webinar on: ROI from AI – Turning Investment into Measurable Impact* (December 2025), lead sponsors of the PIMFA AI Programme Publicis Sapient have developed this FREE 30–60–90 day plan to give wealth managers a clear, de-risked pathway for taking a single AI workflow from concept to measurable business impact in just three months.
The need for a structured, proven approach has never been clearer. During the webinar, member firms told us that 40% do not have a consistent definition of AI ROI, 33% try to measure everything at once, 0% measure revenue uplift, and 75% cite data readiness as the biggest barrier to value. A further 31% highlighted governance and accuracy concerns. These results reflect a sector-wide truth: firms are investing in AI, but lack the focus, foundations and frameworks needed to turn ambition into measurable outcomes.
This 30–60–90 plan has been designed to solve exactly that.
Whether you are beginning your AI journey or scaling at pace, focusing on one high-value use case, establishing minimum viable data and governance foundations, and delivering a working prototype within 30 days creates early momentum and clarity. The following 60 days harden the solution through real-world testing, integration and oversight, culminating in a parallel run that proves tangible ROI — faster cycle times, improved accuracy, greater capacity and stronger control.
The result?
A repeatable, scalable model that enables your firm to embed AI safely, confidently and with quantifiable value.
This plan isn’t theory, it’s the proven process Publicis Sapient are already deploying with wealth and asset managers to turn AI ambition into repeatable, measurable ROI in weeks, not years. This plan reflects the sort of practical support we provide to senior leaders on the AI Leaders Incubator Programme, no theory, no coding, just hands-on guidance and applied frameworks to help firms unlock real ROI from AI.
Click here to access the webinar.
GUIDELINES FOR USING THIS 30–60–90 DAY AI SCALING PLAN
Pick ONE workflow and treat it as a business investment.
This plan only works if you focus. Select a single workflow with a clear and defensible link to cost reduction, risk mitigation, or revenue enablement. Do not run multiple workflows in parallel. Depth creates value; breadth creates noise.
Appoint a single owner accountable for ROI.
Every workflow must have one accountable business owner with authority to make trade-offs and decisions. AI initiatives fail when ownership is shared; they scale when accountability is clear.
Define ROI before you build anything — and anchor it financially.
Before any build activity begins, define success in terms the Board recognises:
- Cost: reduction in cost-to-serve, manual effort, or rework
- Risk: fewer errors, stronger controls, improved auditability
- Revenue: increased capacity, faster onboarding, improved client outcomes
Operational metrics (cycle time, accuracy, capacity) are enablers — they must ladder directly to one of these three outcomes.
Use minimum viable data, not perfect data.
Your data will never be perfect. Waiting for perfection guarantees inertia.
Define the minimum viable data required to prove value in 90 days and iterate from there. Firms that succeed improve their data estate because they deliver value, not before.
Embed governance early to accelerate scale later.
Governance is not an obstacle; it is what allows AI to move safely into production.
Define escalation thresholds, confidence scores, human-in-the-loop controls, and risk ownership from day one. What is governed early scales faster.
Expect weekly iteration, not linear delivery.
This plan depends on rapid learning cycles. If metrics are not improving week-on-week, pause and adjust. Progress is measured by outcomes moving, not activities completed.
Treat KPIs as non-negotiable decision tools.
Track a small number of metrics that matter:
- Cost removed
- Risk reduced
- Capacity or throughput created
If these metrics do not move, pivot. AI scaling is a business discipline, not a technology exercise.
Communicate early, clearly, and consistently.
Bring operations, risk, compliance, and frontline teams into the journey from day one. Silence creates resistance; transparency builds trust and adoption.
Prove value in parallel before declaring success.
The final 30 days must demonstrate performance against real operating conditions. Parallel runs - agent vs. human - are essential to validate impact and build executive confidence.
Reuse the pattern, don’t reinvent it.
Once the first workflow proves ROI, lift and replicate the model. This is how firms move from pilot > portfolio > enterprise scale.
0–30 DAYS: SET THE VALUE AGENDA & BUILD THE FIRST WORKING MODEL
Objective: Create absolute clarity on where value will come from, align stakeholders on ROI, mobilise the minimum viable dataset, and deliver a functioning v1 that demonstrates AI is real, feasible, and directly linked to a P&L driver.
Focus Area | Executive-Level Questions | Board-Ready Deliverables | Leadership Roles Required | KPIs (Board-Level)
Value & Workflow Selection
- Executive-Level Questions
- Which workflow creates meaningful P&L impact within 90 days?
- Where is the friction costing us time, money, or control?
- Board-Ready Deliverables
- Prioritised workflow with value hypothesis
- Economic baseline (cost, cycle time, error rates)
- Executive Value Charter (sponsor, outcomes, decision gates)
- Leadership Roles Required
- Business workflow owner
- COO/Operations sponsor
- Finance partner
- KPIs (Board-Level)
- Workflow approved for ROI delivery
- Baseline metrics signed off
ROI Definition & Success Metrics
- Executive-Level Questions
- What does “success” mean in financial terms?
- Which metric will shift first: cost, risk, capacity, client experience?
- Board-Ready Deliverables
- Defined ROI model (cost-out, capacity release, risk reduction)
- KPI dashboard v0
- Leadership Roles Required
- CFO / Finance lead
- Data analyst
- KPIs (Board-Level)
- ROI metric agreed (e.g., 30–50% cycle-time target)
- Measurement framework approved
Minimum Viable Data (MVD)
- Executive-Level Questions
- What data is critical vs. optional?
- What gaps exist and which are non-blocking?
- Board-Ready Deliverables
- Data inventory + quality scoring
- MVD specification
- Data access confirmed
- Leadership Roles Required
- Data owner / Data steward
- Data engineer
- KPIs (Board-Level)
- MVD delivered (≥80% completeness)
- No blocking data dependencies
Human + Agent Operating Model
- Executive-Level Questions
- How should work be redistributed between people and AI?
- What oversight ensures safety from day one?
- Board-Ready Deliverables
- Human-in-loop model
- Preliminary risk controls & escalation paths
- Regulatory considerations flagged
- Leadership Roles Required
- COO / Ops lead
- Risk & Compliance SME
- KPIs (Board-Level)
- Governance sign-off received
- Initial control thresholds approved
Agent Build (Prototype v1)
- Executive-Level Questions
- What is the simplest version that proves feasibility?
- Which early indicators show this is viable?
- Board-Ready Deliverables
- Functional prototype
- Early accuracy and latency metrics
- Demo for leadership
- Leadership Roles Required
- KPIs (Board-Level)
- Prototype delivered within 30 days
- Accuracy meets minimum threshold (e.g., 70%+)
Integration Feasibility
- Executive-Level Questions
- What is the lowest-friction integration path?
- What must we avoid to keep velocity high?
- Board-Ready Deliverables
- Integration plan (phased: manual → API)
- Confirmed access to key systems
- Leadership Roles Required
- IT integration lead
- Security
- KPIs (Board-Level)
- Integration readiness achieved
- Access to required systems confirmed
Controls & Guardrails
- Executive-Level Questions
- What level of risk are we prepared to accept in a pilot?
- How will we monitor quality from day one?
- Board-Ready Deliverables
- Guardrail framework v1
- Calibration benchmarks for model behaviour
- Leadership Roles Required
- KPIs (Board-Level)
- Thresholds defined and approved
- Drift monitoring approach validated
Stakeholder Alignment & Change Readiness
- Executive-Level Questions
- Who must be aligned now to prevent blockers later?
- What communications reduce anxiety and resistance?
- Board-Ready Deliverables
- Stakeholder map + engagement plan
- Leadership briefings
- Pilot user training materials
- Leadership Roles Required
- Change management
- L&D lead
- KPIs (Board-Level)
- Adoption readiness score (≥70%)
- Stakeholder alignment confirmed
30–60 DAYS: INDUSTRIALISE THE PILOT & PROVE RELIABILITY
Objective: Strengthen the agent, integrate with existing systems, embed guardrails, and validate performance in real workflows to ensure the solution is accurate, safe, and operationally scalable.
Focus Area | Executive-Level Questions | Board-Grade Deliverables | Leadership Roles Required | KPIs (Executive/Board-Level)
Agent Hardening
- Executive-Level Questions
- Does the agent demonstrate consistent, explainable behaviour under varied scenarios?
- Where must we improve reasoning, accuracy, or stability before operational exposure?
- Board-Grade Deliverables
- Agent behaviour pack (v1→v2)
- Workflow orchestration logic refined
- Performance improvement log
- Leadership Roles Required
- AI engineering lead
- Business SMEs
- Ops sponsor
- KPIs (Executive/Board-Level)
- Accuracy uplift trending to target (e.g., 70% → 85–90%)
- Reduction in output variance across scenarios
Integration Readiness
- Executive-Level Questions
- Is integration secure, stable, and low risk?
- Are we removing manual workarounds that slow throughput?
- Board-Grade Deliverables
- Integration readiness report
- API connections + system access confirmed
- Security validation completed
- Leadership Roles Required
- IT integration lead
- Enterprise security
- Architecture
- KPIs (Executive/Board-Level)
- Integration stability > 98%
- Latency within acceptable thresholds
- Zero open critical integration risks
Controls & Guardrails
- Executive-Level Questions
- Are the right governance and oversight controls in place to protect clients and the firm?
- How do we monitor drift, escalation patterns, and accuracy transparently?
- Board-Grade Deliverables
- Guardrail & escalation framework (v2)
- Drift monitoring process
- Compliance review + conditional sign-off
- Leadership Roles Required
- Risk lead
- Compliance SME
- QA & model validation
- KPIs (Executive/Board-Level)
- Declining escalation rate
- Error reduction trend > X%
- All high-risk controls in place ahead of parallel run
Real-World Scenario Testing
- Executive-Level Questions
- How does the agent perform under real operational complexity—not just test cases?
- Are we improving speed, quality, and user confidence every week?
- Board-Grade Deliverables
- Scenario library
- Iteration logs + weekly improvements
- Updated model version deployed
- Leadership Roles Required
- Operations teams
- Pilot users
- QA testers
- KPIs (Executive/Board-Level)
- Time-on-task reduction week-over-week
- Internal CSAT/NPS improving
- Declining exception rate
Stakeholder Readiness & Change Alignment
- Executive-Level Questions
- Are frontline teams trained, confident, and ready to adopt the new human+agent model?
- Have we proactively removed organisational blockers?
- Board-Grade Deliverables
- Training programme updated
- Communications plan (ops, risk, leadership)
- Change readiness scorecard
- Leadership Roles Required
- Change management lead
- L&D
- Process owner
- KPIs (Executive/Board-Level)
- Readiness score > 75%
- Stakeholder alignment confirmed across Ops, Compliance, Risk
60–90 DAYS: DEMONSTRATE BUSINESS IMPACT & COMMIT TO SCALE
Objective: Run a fully supervised parallel process, quantify financial impact, and produce the evidence pack required for leadership to approve broader rollout across additional workflows.
Focus Area | Executive-Level Questions | Board-Ready Deliverables | Leadership Roles Required | KPIs (Board-Level)
Pre-Production Deployment
- Executive-Level Questions
- What operational, risk, and infrastructure criteria must be satisfied before controlled release?
- Are there any stability or security concerns that could impact production readiness?
- Board-Ready Deliverables
- Pre-production readiness report
- Risk & controls verification
- Deployment checklist signed off by Ops, Risk, and IT
- Leadership Roles Required
- Engineering lead
- IT operations
- Security & Risk
- KPIs (Board-Level)
- System resilience: uptime > 99%
- Zero critical failures
- All high-risk items closed pre-deployment
Supervised Parallel Run
- Executive-Level Questions
- Does the agent deliver consistent, decision-grade output against human benchmarks?
- Where does agent performance exceed or fall short of current processes?
- Board-Ready Deliverables
- Parallel run results pack (agent vs human)
- Exception & deviation reports
- Quality & consistency analysis
- Leadership Roles Required
- Operations team
- Data quality lead
- AI engineers
- KPIs (Board-Level)
- Cycle-time reduction 30–50%+
- Accuracy & consistency uplift (target X%)
- Reduction in manual touchpoints
ROI Validation & Executive Impact Case
- Executive-Level Questions
- What tangible financial impact has been demonstrated today?
- Does the value case justify scaling investment?
- Board-Ready Deliverables
- ROI dashboard (before/after)
- Financial impact analysis (cost, capacity, risk)
- Executive impact narrative for Board approval
- Leadership Roles Required
- CFO / Finance lead
- BI/analytics lead
- KPIs (Board-Level)
- Cost-to-serve reduction (validated)
- Hours of capacity released
- Error reduction % improvement
Scale Blueprint & Governance Approval
- Executive-Level Questions
- What is the enterprise-wide pattern we can now replicate?
- What governance and risk decisions must be confirmed before wider rollout?
- Board-Ready Deliverables
- Enterprise scale roadmap
- Reusable architecture & operating model
- Governance approval pack
- Leadership Roles Required
- Product owner
- Risk & compliance
- CTO / COO sponsor
- KPIs (Board-Level)
- Next workflow approved for scale
- Governance sign-off completed
- Funding or capacity allocation secured
Change, Adoption & Embedding
- Executive-Level Questions
- Are teams ready to adopt the workflow as business-as-usual?
- Have we updated controls, processes, and training for a safe and confident rollout?
- Board-Ready Deliverables
- Final training rollout
- Updated SOPs + risk procedures
- Adoption & readiness scorecard
- Leadership Roles Required
- Training lead
- Process owners
- Ops leadership
- KPIs (Board-Level)
- Adoption rate 80%+
- Process compliance > 95%
- No major operational incidents logged
THE AI LEADERS INCUBATOR PROGRAMME
PIMFA and Publicis Sapient have joined forces as partners to create the AI Leaders Incubator Programme, a powerful two day learning experience for senior leaders in wealth management.
With the hands-on support of industry experts, you will learn to design, test and deploy real AI use cases that deliver measurable business results. Using proven frameworks and practical labs, you will define your own roadmap to ROI, building the confidence, capability and conviction to turn insight into execution and execution into impact.
No coding or data-science background is required. All you need is the ambition to understand how AI aligns with your firm’s size, data maturity and risk appetite and the willingness to select scalable use cases that deliver measurable, defensible results.
To find out more about the AI Leaders Incubator Programme.
ABOUT PUBLICIS SAPIENT
Publicis Sapient is a global technology leader in that provides enterprise AI platforms and services. With over 30 years of digital business transformation experience, they enable enterprise clients to transform how they operate and serve their customers, unlocking new value and enabling them to thrive in an AI-driven world. Their platforms use AI built off this deep enterprise context to untangle legacy complexity and build agentic solutions to streamline operations and strengthen risk and regulatory performance. The combination of proprietary AI platforms and the expertise of their teams bring hands-on experience to deliver faster and more effective outcomes through solutions that are specific to the unique needs of global enterprises, including wealth and asset managers. Publicis Sapient is the technology hub of Publicis Groupe, uniting 20,000 people worldwide. For more information, visit publicissapient.com.
As co-creators of the AI Leaders Incubator Programme, Publicis Sapient has worked alongside PIMFA to design the curriculum, shape the learning journey, and bring real-world use-cases and practitioner expertise directly into the programme.