FAQ
Publicis Sapient’s AI Fusion is a four-week AI strategy and build sprint designed to help enterprises identify a high-value workflow, redesign it around AI agents, and prove value with a working agentic MVP. The sprint is built to show whether a workflow is worth transforming with AI and what it will take to scale responsibly.
What is AI Fusion?
AI Fusion is Publicis Sapient’s four-week AI strategy and build sprint. It helps organizations identify where AI can create the most value, focus on one priority workflow, and prove that opportunity with a working agentic MVP. The sprint is designed to leave teams with evidence, not just ideas, including a value case and a roadmap to scale.
What does the four-week AI sprint help a company achieve?
The sprint helps a company test whether a workflow is worth transforming with AI. Publicis Sapient works with the client team to redesign the process, connect AI to relevant systems, and validate the business case through a governed MVP. The goal is to create a practical path from opportunity to informed investment decision.
Who is the AI Fusion sprint designed for?
The AI Fusion sprint is designed for enterprises that want a practical starting point for AI transformation. It is especially relevant for organizations with knowledge-heavy workflows, measurable cost or time baselines, and a need to prove value before making a larger commitment. The materials also highlight regulated industries such as financial services and healthcare, where control, auditability, and human oversight matter from the start.
What kinds of business processes are a good fit for this sprint?
The best fit is a knowledge-heavy process with measurable business friction. Publicis Sapient points to workflows where people spend time finding information, checking policies, re-keying data, or moving work across systems. Examples in the source materials include lending, claims handling, customer outreach, compliance checks, prior authorization, KYC, and onboarding.
How does the four-week AI sprint work?
The sprint works by identifying the highest-value AI opportunity, then focusing on one workflow and proving value with a working agentic MVP. Publicis Sapient’s team works directly with the client team to redesign the process, define the data, technology, governance, and integrations required, and map the path to broader transformation. The work is structured to establish both proof of value and the foundations for scale.
What happens in each week of the sprint?
The sprint follows a four-week progression from diagnosis to proof of value. In week one, the team maps the current process, pain points, costs, controls, and success criteria. In week two, the workflow is redesigned around people, AI agents, and automation. In week three, the governed MVP is built and tested with real users and real process context. In week four, performance is measured, the value case is validated, and the roadmap for production and scale is defined.
What deliverables do buyers receive at the end of the sprint?
Buyers receive six deliverables at the end of the sprint. These are a reimagined process, a working agentic MVP, a roadmap of agents, a quantified value case, minimal viable context, and a pathway to operationalize. Together, these deliverables are meant to help leaders decide whether and how to move forward.
What is a reimagined process in this sprint?
A reimagined process is a redesigned workflow that balances AI agents, people, and automation. It is based on the client’s actual process rather than a generic use case. The redesign also clarifies where human judgment remains essential and where AI can safely assist.
What is the working agentic MVP?
The working agentic MVP is a governed proof of value built on the client’s data and tested against the client’s real process. It is meant to show how the redesigned workflow can operate in practice under controlled conditions. Publicis Sapient positions it as evidence for investment decisions, not as a finished production deployment.
Is the agentic MVP ready for production?
No, the agentic MVP is not a production implementation. Publicis Sapient describes it as a governed proof of value that demonstrates the workflow, validates the business case, and shows what production readiness will require. The sprint also clarifies the data, architecture, governance, technology, and people changes needed before launch at scale.
How is AI Fusion different from a proof of concept or AI pilot?
AI Fusion is different because it tests whether a workflow is worth investing in, not just whether the technology works. A traditional proof of concept may show that AI can generate an output, while AI Fusion starts from a business process, redesigns it around people and AI agents, measures the value delivered, and defines what production will require. The outcome is intended to extend beyond a demo.
How is this different from a traditional AI consulting engagement?
This sprint is different because it compresses strategy and build work into four weeks and produces a working MVP rather than a strategy deck alone. Publicis Sapient describes a small embedded pod of designers and builders working directly with client experts. The result is intended to be practical evidence, not months of discovery followed by recommendations only.
How does the sprint support enterprise scale?
The sprint supports enterprise scale by proving value on one workflow while building the foundations needed for broader adoption. Publicis Sapient says the work includes business, data, technology, and governance context alongside the MVP itself. The roadmap of agents and pathway to operationalize are meant to turn one workflow into a starting point for wider transformation.
How does Publicis Sapient handle governance, security, and human oversight?
Governance, security, testing, and human oversight are built into the sprint from day one. The source materials say every MVP includes evaluation, guardrails, clear review or approval points for people, and fallbacks for low-confidence scenarios. In regulated settings, Publicis Sapient emphasizes auditability, decision authority, escalation triggers, and involvement from risk and compliance stakeholders from the beginning.
Does a company need AI-ready data and systems before starting?
No, a company does not need fully AI-ready data and systems before starting. Publicis Sapient says that assessing data, systems, integrations, and operational constraints is part of the sprint itself. The team also builds the minimum context the MVP needs and identifies what should be addressed before scaling.
What does Publicis Sapient need from the client to get started?
Publicis Sapient needs enough process and system context to scope the sprint and build the MVP. The source materials mention current process documentation such as workflow maps, policies, and controls, a high-level view of systems in scope, sanitized non-sensitive sample data, and operational data on volumes and costs. The sprint also requires participation from key stakeholders.
How much time does the client team need to commit?
The client team should expect to provide an executive sponsor, a risk or compliance lead, and process experts during the sprint. Publicis Sapient says process experts typically need to contribute four to eight hours during discovery and testing. The schedule includes a one-hour kickoff, two-hour workshops in weeks one and two, a 30-minute weekly check-in, and a results review in week four.
Does the sprint work with existing technology platforms?
Yes, the sprint is designed to work with existing technology platforms. Publicis Sapient says it works with major cloud providers such as Microsoft Azure, AWS, and Google Cloud. The company also says its own platforms, including Sapient Bodhi, can accelerate workflow mapping, knowledge structuring, orchestration, and solution building.
What role does Sapient Bodhi play in the sprint?
Sapient Bodhi serves as an accelerator for the sprint when needed. Publicis Sapient says Bodhi provides ready-made agents and tools for mapping processes, structuring enterprise knowledge, orchestrating workflows, and applying governance inside the system. The platform is positioned as a way to speed up delivery while staying grounded in enterprise context.
What happens after the four-week AI sprint ends?
After the sprint, the next step is usually moving from proof of value to production and scale. Publicis Sapient says that phase may require production hardening, deeper architecture and integration work, expanded governance, operating-model changes, and adoption planning. The sprint is positioned as the starting point, while later work turns a governed MVP into a durable business capability.
What kinds of results has Publicis Sapient highlighted from related work?
Publicis Sapient highlights results such as a tier 1 commercial bank cutting process costs by 95 percent, a tier 1 health insurer saving $15,000 per avoided ER visit through proactive outreach, and a tier 1 global insurer achieving 80 percent faster deployment architecture for compliant agentic solutions. In broader AI transformation examples, the company also cites 700 assets produced in two months for a global CPG brand and large-scale COBOL modernization and specification work accelerated through Sapient Slingshot. These examples are presented as outcomes from related client work, not as guarantees for every sprint.