Elevate customer and employee experiences with generative AI-powered copilots and agents

Introduction

In the realm of customer service, bots or chatbots were heralded as game-changers. These technologies promised to streamline customer interactions, reduce operational costs, and enhance user satisfaction. However, reality has fallen short of these expectations for many organizations and consumers. Traditional chatbots often struggle with understanding even basic queries and providing satisfactory responses, leading to customer frustration, lost sales, and customer churn.

Generative AI-powered copilots and agents, however, have the potential to transform this landscape by offering more sophisticated, natural, contextually aware, autonomous and personalized interactions for customers and employees alike.

Opportunities with virtual agents

As a reminder, chatbots present numerous opportunities for enhancing customer support. Here are some key benefits:

1. Answering common queries: Chatbots can handle a wide range of routine inquiries, such as account information, order status, and troubleshooting steps. This capability ensures customers receive immediate responses to their questions, improving their overall experience.
2. Reducing wait times: By managing multiple interactions simultaneously, chatbots significantly reduce wait times. Customers no longer need to endure long hold times or wait for email responses, leading to higher satisfaction levels.
3. Freeing up human agents: With chatbots handling routine tasks, human agents can focus on more complex and nuanced issues that require a personal touch. This not only improves the efficiency of the support team but also enhances the quality of service provided to customers.
4. 24/7 availability and scalability: Chatbots are available around the clock, providing support even outside of regular business hours. This ensures customers can get assistance whenever they need it, regardless of time zones or peaks due to promotional campaigns.
5. Personalization: Advanced chatbots can leverage customer data to provide personalized responses and recommendations. This level of customization enhances the customer experience and fosters loyalty.
6. Data collection and analysis: Chatbots can collect valuable data on customer interactions, preferences, and pain points. This information can be analyzed to gain insights into customer behavior and improve service strategies.

Challenges with current chatbots

However, for all their promise, chatbots have often fallen short in realizing these benefits.

According to a 2024 survey by Forrester Consulting, nearly half of the 1,500 global consumers polled expressed frustration with chatbots, with many characterizing their interactions as negative. (Source: One Negative Chatbot Experience Drives Away 30% Of Customers ).

Traditional chatbots face several significant challenges that limit their effectiveness. They often struggle with the complexities of human language, including slang, idioms, and context-dependent meanings, leading to misunderstandings and incorrect responses. Many are designed for simple, repetitive tasks and falter when handling complex or multi-step queries, necessitating escalation to human agents. Their generic responses can make interactions feel impersonal, failing to provide empathy and meet customer expectations for personalized experiences. Additionally, chatbots have difficulty maintaining context within a single conversation and across multiple sessions, resulting in disjointed responses. Moreover, many chatbots are not equipped to securely handle sensitive customer information, which raises concerns about data privacy and security.

How generative AI copilots and agents are different

Generative AI-powered copilots and agents represent a significant advancement over traditional chatbots. Here’s how they differ:

1. Advanced natural language processing (NLP): Generative AI copilots and agents use sophisticated NLP to understand and generate human-like responses. This allows them to engage in more complex, meaningful, and contextually relevant conversations.
2. Reasoning over large bodies of knowledge: Unlike traditional chatbots, which rely on pre-programmed responses, generative AI agents can reason over extensive datasets – structured and unstructured – as well as from internal and external sources. This enables them to provide accurate and detailed answers to a wide range of queries as well as planning complex tasks.
3. Continuous learning and improvement: Generative AI copilots and agents can learn from interactions and continuously improve their responses. This dynamic learning capability ensures that they become more effective over time.
4. Enhanced personalization: Generative AI copilots and agents can offer highly personalized responses and recommendations by leveraging customer data. This level of customization enhances the customer experience and fosters loyalty.
5. Deterministic and non-deterministic: By infusing a conversation with deterministic and non-deterministic aspects, it’s possible to achieve a combination of precision and creativity within a single interaction.
6. Language translation, speech, and image recognition: Advances in these areas enable generative AI to support multiple languages and provide voice, text, and image-based experiences. This opens additional opportunities for more natural interaction, global customer support, and accessibility.
7. Advanced planning and reasoning: Agents can be fully autonomous and can orchestrate other agents to handle complex multi-step processes.  Leveraging models such as Azure OpenAI o1 allows for deep reasoning and problem solving.

Industry scenarios with generative AI copilots and agents

Generative AI copilots and agents provide opportunities across industries to achieve more complex tasks through multi-turn, contextually aware, and personalized interactions.

Some examples include:

• Finance: As part of financial planning, provide bespoke investment suggestions aligned to market trends and individual financial data. 
• Retail: For personalized shopping consultations based on preferences, skin type, and previous purchases.
• Automotive: For in-car experiences adapted to driver habits and preferences.
• Public services: To handle non-emergency inquiries, report minor crimes, and provide information on police services.
• Healthcare: To provide health advice, book appointments, and manage patient records.
• Education: For tailored learning experiences, adapted to the individual’s pace with custom exercises for the learner’s current level.
• Travel: For planning and booking trip itineraries aligned with personal interests.

An approach for success

While generative AI copilots and agents offer numerous benefits, their rollout needs careful consideration. In the past 18 months, headlines have been made for the wrong reasons, as generative AI has provided rogue responses – opinions on topics outside of their scope, recommendations of competitors, and even swearing at customers. Such incidents highlight the importance of a thorough approach to deploying generative AI.

To successfully roll out a generative AI copilot or agent, consider these high level steps:

1. Define clear objectives and KPIs: Establish what you want your copilot/agent to achieve, the boundary of its skills, and set measurable goals.
2. Design the copilot personality and user experience: Ensure the experience aligns with your brand and provides an intuitive user experience.
3. Choose the right technology: Select a platform that meets your needs, whether it’s a native solution like agents in Dynamics 365, a no-code solution like Microsoft’s Copilot Studio or a more customizable option like Azure AI Studio.
4. Develop and train: Use diverse data sets to avoid bias, train the copilot/agent, and enhance its understanding and response accuracy.
5. Test thoroughly: Conduct extensive internal and user testing to identify and fix any issues.
6. Gated launch: Launch with an internal audience first, e.g., contact center human agents who can extensively test the effectiveness.
7. Monitor and optimize: Monitor the copilot/agent performance and make necessary adjustments to improve its effectiveness.

Microsoft technologies for copilot and agent experiences

Microsoft’s vision is to have a Copilot for every role and function and a world where there may be as many agents in an organization as Word documents. In addition to Microsoft 365 Copilot for general productivity, and role-based copilots for finance, sales, service, and marketing, Microsoft provides process specific agents in Dynamics 365 and a suite of tools for developing bespoke copilots and agents.

Microsoft’s vision is to have a Copilot for every role and function and a world where there may be as many agents in an organization as Word documents. In addition to Microsoft 365 Copilot for general productivity, and role-based copilots for finance, sales, service, and marketing, Microsoft provides process specific agents in Dynamics 365 and a suite of tools for developing bespoke copilots and agents.

In Dynamics 365, Microsoft have previewed 10 agents that include Supplier Communications Agent which optimises the supply chain and minimises disruptions by autonomously tracking supplier performance, identifying and responding to delays thus freeing procurement teams from time consuming manual activities.  The Sales Qualification Agent helps B2B sellers focus their time on the highest priority leads, personalizing emails and guiding customer contact. The Customer Intent and Knowledge Management Agents work hand in hand with customer service representatives to resolve customer issues autonomously and adding knowledge base articles to ensure customers have consistent interactions.

Copilot Studio is a no-code/low-code platform that allows businesses to easily create sophisticated copilots. Copilot Studio integrates seamlessly with other Microsoft services, such as Microsoft 365, Dynamics 365, and Azure. Microsoft also provides more than 1,400 connectors to other systems, enabling a unified approach to building copilots and agents regardless of where the data resides.

Azure AI Studio provides a comprehensive framework for building, deploying, and managing intelligent bots. This service supports multiple channels, including web, mobile, and social media, ensuring businesses can reach their customers wherever they are. Additionally, Azure Cognitive Services enhances chatbot capabilities with advanced NLP, speech recognition, and sentiment analysis, allowing for more natural and engaging interactions.

When deciding between Microsoft Copilot Studio and Azure AI Studio, consider the following:

• Copilot Studio: Ideal for businesses looking for a user-friendly, no-code solution to deploy copilots and agents quickly. It is ideal for scenarios where rapid development and deployment are crucial, and where integration or extension of copilots and agents in Microsoft 365 and Dynamics 365 is beneficial. Copilot Studio provides a fully managed, hosted service with built-in analytics, security, and governance controls. However, there is limited fine-grain control.
  
• Azure AI Studio: Best suited for scenarios that require highly customizable and scalable solutions. It is ideal for complex scenarios that need deep integration with various Azure services, advanced AI capabilities, and leveraging Microsoft Azure’s extensive catalog of foundation models.

Conclusion

Generative AI copilots and agents provide the opportunity to revolutionize customer support and employee experiences by providing natural experiences across every channel. By addressing the challenges of traditional chatbots and leveraging the opportunities presented by generative AI, companies can now deliver value creating experiences.

Microsoft’s suite of technologies, including agents in Dynamics 365, Copilot Studio and Azure AI Studio, enables businesses to build and deploy sophisticated copilots and agents. Successfully embracing these technologies will lead to higher customer satisfaction, improved operational efficiency, and a competitive edge in the market.

To understand how generative AI-powered copilots and agents can transform your customer and employee experience, contact us today for a custom presentation or workshop.

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Food for thought

Capgemini’s recent solution paper, jointly developed with Microsoft, entitled Empower the next generation of customer engagement with generative AI, explores the generative AI opportunities that exist in marketing, sales, customer service, commerce, supply chain, and more and how our expertise, combined with Microsoft’s cutting-edge suite AI solutions, can help our clients automate processes, unlock creativity, and empower employees to collaborate with AI copilots and agents, driving next-level customer engagement.

Empower the next generation of customer engagement with generative AI

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