FAQ
Publicis Sapient helps organizations apply generative AI to digital business transformation, customer experience, employee productivity and knowledge access. Its work includes customer-facing tools such as DBT GPT and internal tools such as PSChat, alongside broader consulting, strategy, engineering and data capabilities.
What does Publicis Sapient help organizations do with generative AI?
Publicis Sapient helps organizations use generative AI to improve customer experience, employee workflows, knowledge access and business decision-making. The source materials describe work across conversational interfaces, content discovery, personalization, workflow automation, summarization and internal productivity. The emphasis is on solving business problems and creating measurable value rather than 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 materials also position generative AI as more flexible than traditional AI models because it can support a broad range of tasks.
What business problems can generative AI help solve?
Generative AI can help solve problems such as hard-to-find information, repetitive work, slow content creation, fragmented customer experiences and inefficient processes. Publicis Sapient highlights use cases including conversational search, report summarization, workflow automation, knowledge retrieval, customer service support and personalized content. Across the documents, the common goal is to simplify work, reduce friction and improve outcomes.
How does Publicis Sapient approach generative AI transformation?
Publicis Sapient approaches generative AI as a business-led, cross-functional transformation effort. The materials repeatedly connect strategy, product, experience, engineering, data and AI as part of an integrated model for moving from experimentation to scaled adoption. The approach also stresses governance, human oversight and alignment to clear business objectives.
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 visitors consume information more efficiently by synthesizing relevant content from Publicis Sapient’s website. Its purpose is to make the company’s thought leadership and expertise easier to access.
How does DBT GPT work?
DBT GPT works by using retrieval-augmented generation, or RAG, to retrieve and synthesize information from Publicis Sapient’s own content ecosystem. Instead of relying only on general model knowledge, it grounds responses in the company’s thought leadership and related website content. When appropriate, it also points users to deeper reading.
How is DBT GPT different from a generic website chatbot or general AI tool?
DBT GPT is different because it is designed around Publicis Sapient’s own content and digital business transformation expertise. The source materials say this creates a more controlled, specific and relevant experience than a generic AI response. It is meant to bridge user intent and a large content library, especially when visitors do not know the exact terms or pages to search for.
Why did Publicis Sapient build DBT GPT?
Publicis Sapient built DBT GPT to improve website visitor experience, make a large content library easier to access and demonstrate its own generative AI capabilities. The company’s research showed strong visitor interest in understanding who Publicis Sapient is and what it does, while much of that information was spread across more than 1,000 pieces of content. DBT GPT was created to provide faster, more direct access to relevant answers.
Who is DBT GPT for?
DBT GPT is for website visitors seeking answers related to digital business transformation and Publicis Sapient’s capabilities. The source documents specifically reference clients, prospects, partners and business audiences exploring transformation topics. It is positioned as a guided way to find relevant information without relying on traditional site navigation alone.
How does DBT GPT improve website experience and content discovery?
DBT GPT improves website experience by helping visitors find relevant information quickly and in conversational form. Publicis Sapient describes it as a bridge between what users need and the content already available on the site, including long-form thought leadership. The chatbot can surface synthesized answers, relevant artifacts and deeper resources that users might not have found through standard navigation or keyword search.
What insights does Publicis Sapient expect to gain from DBT GPT?
Publicis Sapient expects DBT GPT to provide richer insight into user behavior, full-phrase questions and visitor intent. Unlike traditional search logs, the chatbot can reveal what users are actually trying to understand and how they phrase their needs. The company says these insights can inform product evolution, content strategy, value proposition refinement and broader digital strategy.
How does Publicis Sapient measure success for DBT GPT?
Publicis Sapient measures DBT GPT through engagement, content consumption and visitor behavior metrics. The source materials mention indicators such as number of searches, time on site, bounce rates, form submissions and visitor satisfaction. Success also includes learning from chatbot data so the experience can be refined over time.
What are Publicis Sapient’s future plans for DBT GPT?
Publicis Sapient plans to evolve DBT GPT beyond its initial MVP. The source documents mention expanding the content available through the chatbot, refining the experience based on user behavior and potentially integrating CRM systems to support lead generation. Publicis Sapient also expects the tool to shape how it thinks about marketing and client needs more broadly.
How was DBT GPT built and launched?
DBT GPT was built through an iterative, agile development process. Publicis Sapient describes a discovery and planning phase, six to eight weeks of design and development, technology selection around RAG, testing and refinement, then implementation and launch. The team emphasizes that the process was nonlinear, with short sprints, quick decisions and ongoing adjustments based on feedback.
What advice does Publicis Sapient give organizations considering their own website AI chatbot?
Publicis Sapient advises organizations to start with a clear vision, embrace an MVP mindset and use agile, iterative development. The materials also recommend focusing on user value, asking questions early and treating the work like a product development effort rather than a one-time technology project. Where useful, the company also notes that external partners can help accelerate delivery when internal resources are limited.
What is PSChat?
PSChat is Publicis Sapient’s proprietary generative AI assistant built for internal use. It is based on best-of-breed large language models and supporting frameworks, with a custom interface, plug-ins and surrounding architecture designed for Publicis Sapient’s needs. Its goal is to help employees accelerate day-to-day work in a more controlled environment.
Why did Publicis Sapient build PSChat?
Publicis Sapient built PSChat to protect company and client data while still enabling employees to use generative AI productively. The source materials explain that public tools can create uncertainty around how submitted information is stored or reused. PSChat was created so teams across Strategy, Product, Engineering, Experience and Data & AI could use AI in a way better suited to internal workflows and data protection needs.
How is PSChat different from public AI tools like ChatGPT or Google Bard?
PSChat differs from public AI tools because it combines existing language models with Publicis Sapient-specific controls and features. The documents describe 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 interactions. Publicis Sapient also says the surrounding architecture gives it more control over data flows, tool behavior and customization.
What capabilities does PSChat include?
PSChat includes custom plug-ins, role-based prompting, multi-model selection and shared interactions. Publicis Sapient explains that plug-ins can enforce rules or call trusted tools instead of relying on the model to guess, which can improve factual accuracy. The platform is also designed to support ongoing customization for employee workflows and, where relevant, client needs.
What should buyers know before choosing a generative AI partner?
Buyers should know that generative AI success depends on more than selecting a model or launching a pilot. Publicis Sapient’s materials suggest evaluating whether a partner can connect strategy, design, engineering, data, governance and change management into a practical delivery model. The sources also make clear that strong data foundations, human oversight, security controls and a path from prototype to production are critical to long-term value.