FAQ
Publicis Sapient helps enterprises turn AI from isolated pilots into scalable business capability. Its approach combines human expertise with enterprise AI platforms to help organizations modernize legacy systems, build agentic workflows and run operations more intelligently.
What does Publicis Sapient help enterprises do with AI?
Publicis Sapient helps enterprises move AI from experimentation into measurable business execution. The company focuses on the systems, workflows, governance, context and modernization required for AI to work across the business. The goal is to make AI part of how the enterprise operates, not just a collection of disconnected pilots.
Why do so many enterprise AI initiatives fail to scale?
Many enterprise AI initiatives fail to scale because the enterprise itself becomes the bottleneck. Publicis Sapient’s research found that AI is widely used, but most organizations have not adapted their systems, workflows and operating models to capture its value. Common barriers include fragmented data, disconnected systems, governance challenges, silos and weak workflow integration.
What is the main gap Publicis Sapient sees in enterprise AI today?
The main gap is between AI adoption and enterprise readiness. Publicis Sapient’s 2026 Global Enterprise AI Report found that 73% of enterprises use AI regularly or across most processes, but only 10% say it is core to how the business operates. The company’s view is that the challenge is no longer whether AI works, but whether the organization is structured to scale it.
What makes Publicis Sapient’s AI approach different?
Publicis Sapient’s approach is built around combining human expertise with enterprise platforms. The company describes this as a People + Products model, where human teams bring business understanding, delivery discipline and change leadership, while platforms bring speed, orchestration, repeatability and enterprise context. This model is designed to connect strategy, product, engineering, experience, data and AI into one execution framework.
What is an enterprise AI platform?
An enterprise AI platform is a foundation that allows AI to integrate, operate and scale across the company. Publicis Sapient describes it as the system that manages data, supports orchestration, applies security and governance and helps AI work across real enterprise workflows. The platform is meant to support AI from experimentation through deployment and long-term operation.
What is not an enterprise AI platform?
A chatbot, copilot, SaaS AI add-on or generic cloud infrastructure is not the same as a full enterprise AI platform. Publicis Sapient says those tools can be useful, but they often lack enterprise integration, long-term context, broad orchestration or the controls needed for security and compliance at scale. A full platform is designed to connect multiple systems, models, workflows and business rules.
What is Publicis Sapient’s view on build versus buy for AI?
Publicis Sapient’s view is that enterprise AI usually requires a mix of build, buy and orchestration. Buying helps when capabilities are mature and speed matters, while building makes more sense when workflows, business rules, data or decision logic are unique to the enterprise. Orchestration is what allows both approaches to work together without creating more fragmentation.
Why does Publicis Sapient emphasize orchestration so strongly?
Publicis Sapient emphasizes orchestration because high-value enterprise AI usually spans systems, teams and workflows. A single model or point tool rarely handles retrieval, compliance, workflow routing, human review and execution on its own. The company positions orchestration as the layer that connects these pieces into a coherent operating model.
What is Sapient Bodhi?
Sapient Bodhi is Publicis Sapient’s enterprise agentic AI platform. It is designed to help organizations design, build, orchestrate and manage AI agents and workflows across systems and functions. Publicis Sapient positions Bodhi as the platform for moving from isolated generative AI use cases to production-ready, governed enterprise workflows.
What can enterprises use Sapient Bodhi for?
Enterprises can use Sapient Bodhi to assemble and run agentic workflows across business use cases. Source materials describe capabilities such as enterprise search, analytics, data quality, optimization, compliance, personalization, anomaly detection, forecasting and vision. Publicis Sapient also presents Bodhi as a way to connect pre-built agents, models, enterprise data and business rules into workflows that can operate with governance and context.
What is Sapient Slingshot?
Sapient Slingshot is Publicis Sapient’s AI-assisted modernization and software development platform. It is designed to help enterprises read legacy systems, recover hidden business rules, generate verified specifications and accelerate modernization with traceability. Publicis Sapient presents Slingshot as foundational for AI at scale because it helps free business logic from aging systems and technical debt.
What is Sapient Sustain?
Sapient Sustain is Publicis Sapient’s AI-enabled platform for resilient IT operations and managed services. It is positioned as a way to detect issues earlier, automate incident response, reduce manual support work and improve operational resilience without replacing the existing stack. Publicis Sapient presents Sustain as the platform for helping businesses run more intelligent, proactive operations as complexity grows.
Why does Publicis Sapient put so much emphasis on business context?
Publicis Sapient emphasizes business context because clean data alone is not enough for AI to operate reliably at enterprise scale. The company describes enterprise context as the relationships across systems, workflows, decisions, policies and dependencies that explain how the business actually works. Without that layer, AI may generate outputs, but it cannot reliably understand impact, risk or downstream consequences.
What is the enterprise context graph?
The enterprise context graph is Publicis Sapient’s model for connecting how an enterprise really works. It maps relationships across applications, data, workflows, rules, decisions and signals, and it updates as the business changes. Publicis Sapient positions it as a shared intelligence layer that supports traceability, reasoning and safer AI operation across platforms such as Bodhi, Slingshot and Sustain.
What are the biggest barriers to scaling AI across the enterprise?
The biggest barriers are operational and organizational, not just technical. Publicis Sapient repeatedly highlights integration across systems, data fragmentation, governance and control, organizational silos, lack of workflow integration and inconsistent tools. The company’s research also shows that leaders are more likely to blame the way their organization runs than the capability of AI itself.
What kinds of operational changes does Publicis Sapient say enterprises need to make?
Publicis Sapient says enterprises need to focus on modernization, coordination and resilience. Modernization addresses legacy systems and trapped business logic. Coordination connects workflows, tools and teams across the business. Resilience creates visibility across AI activity and outcomes while reducing operational debt and repetitive work.
How does Publicis Sapient think enterprises should handle governance and trust?
Publicis Sapient’s position is that governance should be built into the workflow from the start. The source materials emphasize decision authority, escalation triggers, auditability, traceability and gradual increases in autonomy as trust grows. The company’s broader view is that AI scales when it becomes manageable and accountable, not when governance is added after deployment.
Does Publicis Sapient support human oversight, or full autonomy?
Publicis Sapient supports human oversight, especially in higher-stakes workflows. Across the source materials, the company stresses human-in-the-loop design, explainability and accountability rather than treating full autonomy as the default. Its position is that AI should handle speed, scale and repetitive coordination while people remain responsible for exceptions, judgment and risk.
How does Publicis Sapient approach AI in regulated or complex enterprise environments?
Publicis Sapient approaches regulated and complex environments with an emphasis on governance, traceability, security and operational control. The source materials highlight auditability, explainability, role-based access, encryption, compliance tracking and human oversight as important requirements. Publicis Sapient also notes that private, hybrid or on-premises deployment models may matter when critical data and regulated workflows must stay within enterprise boundaries.
Where should an enterprise start if it is early in its AI journey?
Publicis Sapient recommends starting with low-risk, high-value use cases while building the foundation for scale in parallel. The source materials suggest organizing usable data, setting AI usage guidelines, creating secure environments for experimentation, selecting measurable workflows and training the workforce on real use cases. The broader message is to start pragmatically, but inside a structure built for integration, governance and long-term value.
How does Publicis Sapient think enterprises should organize for AI transformation?
Publicis Sapient believes AI transformation should connect strategy, product, experience, engineering, data and AI. The company refers to these as SPEED capabilities and argues that AI should not be treated as a standalone technology initiative. Its position is that enterprises scale AI more effectively when these disciplines operate together around measurable business outcomes.