FAQ
Publicis Sapient helps enterprises understand, adopt and scale generative AI and agentic AI for business transformation. Across these materials, the focus is on practical use cases, systems integration, governance, human oversight and enterprise platforms that support measurable outcomes.
What is agentic AI?
Agentic AI is AI designed to act, not just generate. Publicis Sapient describes it as autonomous systems that can make decisions, break down goals into tasks, interact with connected systems and execute multi-step workflows with minimal human intervention.
How is agentic AI different from generative AI?
Agentic AI differs from generative AI because it is built for autonomous action rather than content creation alone. Generative AI is positioned as useful for creating text, images, audio, code and summaries, while agentic AI is meant to plan, decide and carry out work across systems. Publicis Sapient also notes that agentic AI usually requires deeper integration, stronger guardrails and more oversight.
Why does agentic AI matter to enterprises?
Agentic AI matters because it can help enterprises move from insight generation to workflow orchestration. Publicis Sapient says the opportunity is not just faster answers, but faster execution across business processes such as customer service, supply chain, software delivery and internal operations. The company frames this as a meaningful shift in how work gets done.
What business problems is agentic AI meant to solve?
Agentic AI is meant to reduce bottlenecks caused by fragmented systems, repetitive coordination work and slow manual handoffs. Publicis Sapient positions it as especially useful where teams are delayed by disconnected platforms, approvals or data silos. The goal is better responsiveness, lower friction and more consistent execution.
Why is systems integration so important for agentic AI?
Systems integration is critical because agentic AI cannot operate autonomously without access to the systems where data, decisions and actions live. Publicis Sapient repeatedly states that without deep, real-time connectivity across enterprise platforms, autonomy remains theoretical. In practice, that means agentic AI depends on connected applications, reliable data flows and interoperability across legacy and modern systems.
What kinds of workflows are the best fit for agentic AI today?
The best near-term workflows for agentic AI are repetitive, bounded, high-volume and time-sensitive processes. Publicis Sapient highlights examples such as customer service triage, scheduling, booking, documentation, supply chain response, internal task orchestration and software development support. The materials consistently suggest starting where value is clear and risk is manageable.
How does agentic AI work in practice?
Agentic AI works by combining context, planning, system access and execution. Publicis Sapient describes agents that gather information, break work into subtasks, interact with external systems, trigger actions and continue until a broader objective is completed. The emphasis is on chaining actions together rather than stopping at recommendations.
What are the main business benefits of agentic AI?
The main benefits are improved workflow speed, lower manual effort and better responsiveness. Publicis Sapient also ties agentic AI to cost reduction, operational efficiency, smarter customer interactions and faster execution in areas like service, supply chain and software delivery. In the strongest cases, the value comes from connecting insight directly to action.
What are the biggest risks and challenges with agentic AI?
The biggest challenges include poor systems integration, weak data quality, governance gaps and security concerns. Publicis Sapient also calls out risks such as data poisoning, reward hacking and unexpected infrastructure costs. The company’s position is that agentic AI creates more operational risk than assistive AI because it can take real actions across enterprise workflows.
Why does Publicis Sapient emphasize keeping humans in the loop?
Human oversight is essential because businesses remain accountable for AI decisions and actions. Publicis Sapient recommends human-in-the-loop models so people can review, validate, refine or override AI behavior when needed. This is presented as especially important in high-stakes, ambiguous or sensitive workflows.
What is the recommended path from generative AI to agentic AI?
The recommended path is staged rather than all at once. Publicis Sapient advises enterprises to start with insight-rich generative AI use cases, then embed AI into workflows through copilots and conversational tools, and then pilot agentic capabilities in selected high-value processes. In parallel, organizations should strengthen data readiness, integration, governance and workforce adoption.
When should a company use generative AI instead of agentic AI?
A company should use generative AI when it needs faster deployment and support for content-heavy or knowledge-based work. Publicis Sapient points to drafting, summarization, personalization, documentation and customer communications as strong generative AI use cases. Agentic AI is presented as the better fit when the business needs real-time decisions and coordinated action across systems.
When is a custom or proprietary agentic solution worth building?
A custom agentic solution is worth building when the workflow is core to the business, highly complex and time-sensitive. Publicis Sapient says proprietary investment makes the most sense when the process depends on analyzing large amounts of data quickly and when the value of automation justifies the added complexity. For more standardized workflows, the materials suggest third-party tools may be a faster option.
What use cases does Publicis Sapient highlight most often for agentic AI?
Publicis Sapient most often highlights customer service, supply chain, enterprise workflows, software development and application modernization. The materials describe service triage, proactive issue resolution, inventory and logistics response, project workflow coordination and AI-assisted software delivery as leading examples. These use cases are presented as practical starting points because they offer measurable value and clear operational relevance.
How can agentic AI improve customer experience?
Agentic AI can improve customer experience by connecting insight to action across journeys rather than just answering questions. Publicis Sapient highlights service triage and routing, proactive issue resolution, cross-channel journey orchestration, supply-chain-informed service responses and backstage workflow automation. The focus is on continuity and faster resolution, not automation for its own sake.
How can agentic AI improve software development and modernization?
Agentic AI can improve software development by automating parts of code generation, testing, deployment and modernization. Publicis Sapient describes this as a way to reduce bottlenecks, speed delivery and make legacy modernization more efficient. The materials also position software development as one of the clearest examples of agentic AI creating measurable enterprise value.
What is Sapient Slingshot?
Sapient Slingshot is Publicis Sapient’s proprietary AI platform for software development and enterprise system integration. The materials describe it as an ecosystem of AI agents that automates work across the software development lifecycle, including code generation, testing, deployment and modernization. Publicis Sapient positions Sapient Slingshot as better suited than generic coding tools for complex enterprise environments that need context continuity, customization and stronger controls.
What does Publicis Sapient say enterprises need before scaling agentic AI?
Enterprises need connected systems, reliable data, governance and clear operating models before scaling agentic AI. Publicis Sapient emphasizes that fragmented architecture, siloed data and weak oversight will limit or undermine autonomous workflows. The company’s broader message is that successful agentic AI depends as much on enterprise readiness as on model capability.