FAQ
Publicis Sapient helps organizations apply generative AI to customer experience, employee productivity, knowledge sharing and digital business transformation. Its approach combines strategy, product, experience, engineering, data and AI to move from experimentation to secure, scalable business value.
What does Publicis Sapient help organizations do with generative AI?
Publicis Sapient helps organizations use generative AI to improve operations, customer experience, employee workflows and business decision-making. The source materials describe work across customer service, content creation, software development, knowledge management, personalization and internal productivity. The focus is on solving business problems, not adopting AI for its own sake.
What is generative AI?
Generative AI is a type of artificial intelligence that can create new content such as text, images, video or audio. Publicis Sapient describes it as technology that learns from large datasets and generates outputs based on patterns, context and prompts. The documents also note that generative AI can support a broader range of tasks than traditional AI models.
Why are companies investing in generative AI now?
Companies are investing in generative AI now because it is changing how businesses compete, innovate and deliver value. Publicis Sapient frames it as the next stage of the digital revolution, with potential to improve efficiency, engagement and organizational enablement. The materials also emphasize that companies need a clear strategy to stay competitive as the technology evolves.
What business problems can generative AI help solve?
Generative AI can help solve problems related to inefficient processes, hard-to-find information, repetitive work, slow content creation and fragmented customer experiences. Publicis Sapient highlights use cases such as conversational interfaces, summarization, workflow automation, knowledge search, scenario analysis and personalization. Across the documents, the common goal is to simplify work, accelerate delivery and improve decision-making.
How can generative AI improve customer experience?
Generative AI can improve customer experience by reducing friction, increasing personalization and making service more responsive. Publicis Sapient points to uses such as conversational interfaces, dynamic content generation, tailored product recommendations and faster access to relevant information. The documents also describe backstage improvements that help employees serve customers more effectively.
How does Publicis Sapient recommend companies approach generative AI for customer experience?
Publicis Sapient recommends starting with customer needs rather than starting with the technology. The source materials stress understanding the full customer journey, identifying pain points and prioritizing use cases tied to customer outcomes. They also recommend combining top-down strategy with bottom-up experimentation to keep initiatives practical and valuable.
How can generative AI support employee productivity and creativity?
Generative AI can support employee productivity and creativity by reducing manual work and helping employees focus on higher-value tasks. Publicis Sapient describes use cases such as ideation, first drafts, proofing, workflow automation, knowledge retrieval and decision support. The documents consistently position AI as a tool for human-AI collaboration rather than a replacement for employee judgment.
How can generative AI help with knowledge transfer and workforce upskilling?
Generative AI can help capture expertise, accelerate onboarding and make institutional knowledge easier to access. Publicis Sapient highlights AI-powered knowledge bases, conversational training assistants and personalized learning platforms that recommend relevant content in real time. In industries facing retirements and talent shortages, the materials position this as a way to reduce brain drain and improve operational continuity.
How can generative AI help business leaders make decisions?
Generative AI can help leaders make decisions by analyzing information quickly and surfacing useful insights. Publicis Sapient cites examples such as evaluating market trends, customer behavior, sales forecasting, business scenarios and employee sentiment. In this role, generative AI is described as a strategic co-pilot that supports leadership rather than replaces it.
What customer and employee use cases does Publicis Sapient highlight most often?
The most frequently highlighted use cases are conversational interfaces, customer service support, personalization, content generation, summarization, knowledge search, workflow automation and software development support. Publicis Sapient also references form completion, review summarization, marketing asset creation and internal search across large repositories of information. These use cases appear across both customer-facing and internal business functions.
What are the main benefits of generative AI for businesses?
The main benefits described in the source materials are flexibility, efficiency, personalization, digital innovation, cost optimization and stronger use of data. Publicis Sapient also links generative AI to faster development cycles, improved productivity, more relevant customer interactions and quicker access to information. The overall business value is framed as a mix of operational gains, better experiences and new growth opportunities.
What risks should companies consider when adopting generative AI?
Companies should consider risks related to privacy, security, bias, misinformation, legal exposure and overreliance on AI outputs. Publicis Sapient also warns that public tools can expose confidential information if employees paste sensitive data into them without safeguards. Several documents stress the importance of human oversight, validation and clear guardrails.
How does Publicis Sapient recommend managing security, ethics and governance?
Publicis Sapient recommends building governance, risk management and safeguards into generative AI initiatives from the start. The source materials describe standalone or sandboxed environments, strict data handling policies, access controls, model oversight and ethical frameworks for responsible use. The goal is to let organizations innovate while protecting proprietary information and reducing misuse.
What is PSChat?
PSChat is Publicis Sapient’s proprietary generative AI assistant built for internal use. It is described as a secure, organization-specific tool built on best-of-breed large language models with custom architecture, interfaces and plug-ins. The purpose of PSChat is to help employees ideate, automate work and access contextual knowledge without compromising sensitive data.
Why did Publicis Sapient build PSChat?
Publicis Sapient built PSChat to protect company and client data while still enabling employees to use generative AI in day-to-day work. The source documents explain that public AI tools can create uncertainty around how sensitive information is stored or reused. PSChat was created to give employees a controlled environment that supports productivity, knowledge sharing and experimentation.
How is PSChat different from public tools like ChatGPT or Google Bard?
PSChat differs from public tools because it is designed for secure internal use and tailored organizational workflows. Publicis Sapient says PSChat includes custom plug-ins for more accurate answers, an “act as” feature for role-based responses, support for multiple LLMs and a sharing feature for useful prompts and interactions. The documents also emphasize that its architecture gives Publicis Sapient more control over data flows and model usage.
What capabilities does PSChat include?
PSChat includes custom plug-ins, role-based prompting, multi-model selection and shareable interactions. Publicis Sapient explains that plug-ins can connect the assistant to trusted tools or business rules, which can improve factual accuracy and reduce hallucinations. The platform is also designed to be customizable for different employee workflows and client needs.
What is DBT GPT?
DBT GPT is Publicis Sapient’s conversational website AI chatbot focused on digital business transformation. It is described as a conversational AI search experience that helps website visitors find and consume relevant information more efficiently. Instead of only relying on generic model knowledge, it synthesizes content from Publicis Sapient’s own thought leadership.
How is DBT GPT different from a generic website chatbot?
DBT GPT is different because it uses retrieval-augmented generation to retrieve and synthesize content from Publicis Sapient’s own ecosystem. That means answers are grounded in the company’s thought leadership and can point users to deeper reading when appropriate. The source materials position this as a more controlled, specific and relevant experience than a generic chatbot response.
What business value does DBT GPT provide?
DBT GPT is intended to improve visitor experience, make a large content library easier to access and generate better insight into visitor intent. Publicis Sapient says the chatbot can reveal full-phrase questions and richer user behavior data than traditional site search. The documents also present DBT GPT as a way to demonstrate Publicis Sapient’s own generative AI capabilities in practice.
What proprietary AI platforms does Publicis Sapient mention?
The source materials mention PSChat, Bodhi and Sapient Slingshot. PSChat is an internal generative AI assistant, Bodhi is described as an enterprise AI ecosystem with access to pre-vetted large language models and frameworks, and Sapient Slingshot is positioned as a platform that accelerates software development and modernization. Together, these examples show how Publicis Sapient combines proprietary tools with broader transformation services.
What makes Publicis Sapient’s approach to generative AI different?
Publicis Sapient positions its approach as business-led, cross-functional and end-to-end. The company repeatedly points to its SPEED model—Strategy, Product, Experience, Engineering, and Data & AI—as the foundation for connecting strategy, design, build and governance. The documents also emphasize secure implementation, practical use cases, rapid experimentation and measurable business outcomes.
What should buyers know before choosing a generative AI partner?
Buyers should know that generative AI success depends on more than choosing a model or launching a pilot. Publicis Sapient’s materials suggest evaluating whether a partner can connect strategy, data, engineering, governance, experience design and change management into one practical program. The documents also make clear that strong data foundations, human oversight and a path from prototype to production are critical to long-term value.