TMT Digest | Generative AI

How AI Agents are changing Customer Journey

Marketing in the age of Agentic AI

The marketing landscape is undergoing significant transformation, driven by the rise of agentic AI. This new wave of AI goes beyond generating content or answering basic questions. While Generative AI, like ChatGPT, has already made waves by automating content creation and other tasks, agentic AI goes a step further. It empowers AI systems to make decisions and execute actions independently, without requiring constant human prompts. This shift from passive tools to proactive agents marks a new era in marketing, with profound implications for both brands and consumers.

Recent announcements from tech giants like Google (Gemini 2.0), Microsoft (Copilot), and AWS highlight the growing momentum behind agentic AI. These companies are investing heavily in developing more powerful, multimodal generative AI models to support the creation and deployment of increasingly sophisticated AI agents. For marketers, this presents both challenges and opportunities.

The customer journey as we know it is being disrupted by AI agents. To thrive in this new landscape, marketers need to understand how agentic AI is changing the game and proactively adapt their strategies.

Key differences between Agentic AI and Generative AI

Agentic AI systems are built to analyze data, understand context, and act autonomously to achieve specific goals. They leverage powerful computing resources, vast datasets, and advanced machine learning models, including Large Language Models (LLMs), to learn, adapt, and execute complex tasks. This autonomous nature sets them apart from traditional AI tools.

• Autonomy: Agentic AI agents can operate independently, making decisions and taking actions without human intervention. Imagine an AI system that not only analyzes customer data but also automatically adjusts marketing campaigns in real time based on emerging trends and customer behavior.
• Real-Time Adaptation: Agentic AI systems can adapt to changing circumstances and new information instantly.They can learn from each interaction, continuously refining their strategies and improving their performance. This real-time responsiveness allows them to capitalize on fleeting opportunities and address emerging challenges.
• Goal Orientation: Agentic AI agents are programmed with specific objectives, such as optimizing marketing campaigns, increasing customer engagement, or driving conversions. This goal-oriented approach ensures that their actions are aligned with the desired outcomes.

How are Brands leveraging Agentic AI?

In addition to hyperscalers, startups are emerging as AI-agent-building platforms. According to Gartner, by 2028, 33% of enterprise software applications will include agentic AI.

• ThoughtSpot: Thoughtspot is an AI-powered analytics platform for modern data stacks. ThoughtSpot has developed Spotter, an AI Analyst, which uses agentic AI to provide actionable insights. Spotter analyzes large datasets and provides real-time visualizations to identify areas for improvement.
• JPMorgan Chase: Scott Stevens, Executive Director of Global Technology at JPMorgan Chase, in the Data Chief podcast has noted the evolution of business intelligence from a backward-looking approach to one that embraces predictive and live analytics with agentic AI.
• HubSpot: HubSpot is investing heavily in agentic AI for small and midmarket businesses (SMBs). They have launched Agent.AI, a network and marketplace for AI Agents where businesses can test and implement AI Agents that work alongside their teams.
• Salesforce: Salesforce has created Agentforce, a platform that enables users to build AI agents that analyze data, prioritize objectives, and take action. This automates many business functions without the need for human intervention.
• Microsoft: Copilot Studio allows users to create and manage AI agents and connect them to the Copilot platform. They have prebuilt autonomous agents for sales, service, finance, and supply chain departments.
• Google: Google is working on Gemini 2.0, which aims to be a universal assistant and a central hub for AI agents. Google Cloud’s Vertex AI Agent Builder allows developers to create agents and applications with natural language and code. [13]
• SAP: SAP is developing Joule, a virtual assistant, to function as an AI Agent hub.
• IBM: IBM has launched an AI Agent orchestration tool that manages and coordinates the work of multiple AI agents.
• Citizens Bank: Citizens Bank is combining AI agents with automation tools for tasks like email distribution.

How AI Agents are Transforming the Customer Journey

Agentic AI possesses the potential to significantly transform how consumers and brands interact, but whether it will be a full-blown “revolution” remains to be seen. Here’s a breakdown of how agentic AI is poised to reshape these interactions:

• Elevated Customer Experiences: Agentic AI can automate tasks, personalize interactions, and provide 24/7 support, ultimately leading to more efficient and satisfying customer experiences. Imagine AI agents that handle basic inquiries, offer personalized product recommendations, or even resolve issues proactively based on real-time data analysis.
• Shifting Decision-Making Power: As AI agents become more sophisticated, they might take on more decision-making responsibilities on behalf of consumers thus impacting the different stages of the buyer’s journey. Thisraises questions about brand relevance — will brands need to target AI agents as a new kind of “consumer” to ensure they’re included in recommendations and choices?
• Redefining Brand Loyalty: In a world where AI agents act as intermediaries, brands will need to find new ways to foster loyalty. This might involve ensuring their AI agents are aligned with brand values and deliver consistently positive experiences. Creating unique value propositions that resonate with both consumers and their AI assistants. Building trust and transparency into their AI-powered interactions.

Rethinking the Marketing Landscape

Marketers will need to adapt their strategies to this new landscape as brands risk losing direct customer relationships with Agentic AI. This could include developing marketing campaigns that appeal to both humans and AI agents. Understanding the ethical implications of AI-driven marketing and ensuring responsible implementation.

The key takeaway is clear: to thrive in this new era of marketing, brands need to embrace agentic AI and leverage its transformative potential. By understanding its capabilities, addressing ethical considerations, and fostering human-machine collaboration, brands can harness the power of agentic AI to create a future where customer experiences are more personalized, engaging, and impactful than ever before.

• Embrace Data-Driven Decision-Making: Agentic AI thrives on data. Marketers need to ensure they have a robust data infrastructure that captures relevant customer information, tracks behavior, and provides insights to train and guide AI agents.
• Prioritize Personalization at Scale: Agentic AI enables hyper-personalization. Marketers should leverage AI agents to deliver tailored experiences, recommendations, and messages to individual customers throughout their journey.
• Build Trust and Transparency: As AI agents take on more responsibility, trust becomes paramount. Marketers need to be transparent about how AI is being used, ensure data privacy, and design AI systems that are fair and unbiased.
• Cultivate Human-AI Collaboration: The goal is not to replace humans but to augment their capabilities. Marketers should focus on finding the right balance between AI automation and human interaction. Train teams to work alongside AI agents, leveraging their respective strengths to create the best customer experiences.
• Experiment and Iterate: Agentic AI is an evolving field. Marketers should embrace an experimental mindset, piloting new AI-powered solutions, gathering data, and continuously refining their strategies.

While the full impact of agentic AI is still unfolding, the sources indicate a significant shift in consumer-brand interactions is on the horizon. The age of agentic AI is here, and the customer journey is being redefined. Marketers who embrace this transformation, adapt their strategies, and focus on building trust and delivering exceptional customer experiences will be best positioned to thrive in this new landscape.

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