Agentic Customer Engagement is Here

There was a time when customer service meant going into a brick and mortar building and talking to a person face to face. It was time consuming and did not guarantee a solution.

The mail order business brought on the need for the 800 number to contact a merchant. The dot com boom brought customer engagement opportunities directly to our homes. Ios and Android apps brought customer engagement to our fingertips. Yet we still were dependent upon the availability of humans or at least chatbots. Customer service often repressed customer engagement, not enhanced it.

Agents, like Salesforce Agentforce, brought 24 7 customer engagement to us no matter where we are, when it is, or how complicated our issue is. And agents improved customer service!

What’s next?

Robots and drones who deliver our items and answer our questions? Who knows.

AI bots are transforming client relationships and customer service. To achieve unparalleled efficiency, these intelligent systems plan and automate difficult activities, make deft decisions, and blend in seamlessly with current workflows.

Yes, it’s widely believed that AI agents will play a crucial role in the future of customer engagement, offering personalized, efficient, and consistent experiences across various channels. 

Here’s why AI agents are poised to be a key driver in customer engagement:

• Personalized Experiences: AI agents can analyze customer data to understand individual preferences and tailor interactions accordingly, leading to more relevant and engaging experiences. 
• Efficiency and Scalability: AI agents can handle a large volume of inquiries simultaneously, providing instant support and freeing up human agents for more complex issues. 
• Omnichannel Support: AI agents can be integrated across multiple platforms (text, voice, social media, etc.), ensuring a seamless customer experience regardless of the channel. 
• Proactive and Predictive Support: AI agents can learn from customer interactions and anticipate their needs, offering proactive solutions and support before difficult issues arise. 
• Improved Customer Satisfaction: By providing faster, more personalized, and consistent support, AI agents can contribute to higher customer satisfaction and loyalty. 
• Cost Reduction: AI agents can automate routine tasks, reducing the need for human agents (freeing them up for more complicated tasks) and lowering customer service costs. 
• Data-Driven Insights: AI agents can gather valuable data on customer interactions, providing insights that can inform business decisions and improve customer engagement strategies. 
• The 4 P’s of Customer Engagement: Personalization, Predictive Analytics, Proactivity, and Partnership are key elements for successful customer engagement, and AI agents can help businesses achieve these. 
• Self-Service Capabilities: AI agents can empower customers to resolve issues independently through self-service options, reducing the workload on human agents. 
• The Future of Customer Service: The integration of advanced AI technologies will transcend traditional service models, delivering highly personalized and value-driven interactions. 

AI agents are becoming smarter every day, using machine learning and natural language processing to predict customer needs, handle complex queries with empathy and offer real-time, personalized assistance.

How AI Agents Are Redefining Customer Engagement

Marketing is undergoing a seismic transformation. Tectonic shift, if you will. The past decade was dominated by complex tech stacks and data integration—now, AI is shifting the focus back to what truly matters: crafting impactful content and campaigns. Welcome to the era of agentic customer engagement and marketing.

The Rise of Marketing Agents

Unlike traditional customer service agents handling one-to-one interactions, marketing agents amplify human expertise to engage audiences at scale—whether targeting broad segments or hyper-personalized personas. They ensure consistent, high-quality messaging across every channel while automating the intricate backend work of delivering the right content to the right customer at the right time.

This shift is powered by rapid AI advancements:

1. Large Language Models (LLMs) enabled basic AI-generated outputs.
2. Generative AI unlocked dynamic content creation from proprietary data.
3. AI Agents now take it further—autonomously reasoning, acting, and optimizing without constant human prompting.

How Agentic Engagement Amplifies Marketing

Marketing agents don’t replace human creativity—they extend it. Once strategists set guidelines, approve messaging, and define brand voice, agents execute with precision across channels.

At Typeface, for example, AI securely learns brand tones and styles to generate on-brand imagery, text, and videos—ensuring every asset aligns with the company’s identity.

Key Capabilities of Marketing Agents

• Agentic Content: Distribute human-approved content at scale, adapting it for different audiences while maintaining brand consistency.
• Agentic Campaigns: Analyze market data, competitor moves, and past performance to recommend—and even test—optimal strategies.
• Agentic Branding: Monitor brand perception in real time, ensuring consistency while identifying growth opportunities.
• Agentic Creative: Take approved designs and adapt them across formats, freeing teams to explore new ideas.
• Agentic Optimization: Continuously refine campaigns for maximum ROI, adjusting in real time based on performance.

The Human-Agent Partnership

AI agents don’t replace marketers—they empower them. Humans bring creativity, emotional intelligence, and strategic decision-making; agents handle execution, data processing, and scalability.

Marketers will evolve into “agent wranglers”, setting objectives, monitoring performance, and ensuring alignment with business goals. Meanwhile, agents will work in interconnected ecosystems—where a content agent’s blog post triggers a social agent’s promotion, while a performance agent optimizes distribution, and a brand agent tracks reception.

Preparing for the Agent Era

To stay ahead, businesses should:
✅ Start small, think big – Pilot agents in low-risk areas before scaling.
✅ Train teams – Ensure marketers understand agent management.
✅ Build governance frameworks – Define oversight and intervention protocols.
✅ Strengthen data infrastructure – Clean, structured data fuels agent effectiveness.
✅ Maintain human oversight – Regularly audit agent outputs for quality and alignment.

Work with a Salesforce partner like Tectonic to prepare for the Agent Era.

The Future is Agentic

The age of AI-driven marketing isn’t coming—it’s here. Companies that embrace agentic engagement will unlock unprecedented efficiency, personalization, and impact. The question isn’t if you’ll adopt AI agents—it’s how soon.

Ready to accelerate your strategy? Discover how Agentforce (Salesforce’s agentic layer) can cut deployment time by 16x while boosting accuracy by 70%.

The future of marketing isn’t just automated—it’s autonomous, adaptive, and agentic. Are you prepared?

The Future of Customer Experience: AI-Driven Efficiency and Innovation

Businesses have long understood the connection between operational efficiency and superior customer experience (CX). However, the rapid advancement of AI-powered technologies, including next-generation hardware and virtual agents, is transforming this connection into a measurable driver of value creation. Increasingly well-documented use cases for generative AI (GenAI) demonstrate that companies can simultaneously deliver a vastly superior customer experience at a significantly lower cost-to-serve, resulting in substantial financial gains.

From Customer Journeys to Autonomous Customer Missions

To achieve this ideal balance, companies are shifting from traditional customer journeys—where users actively manage their own experiences via apps—to a more comprehensive approach driven by trusted autonomous agents. These agents are designed to complete specific tasks with minimal human involvement, creating an entirely new paradigm for customer engagement. While early implementations may be rudimentary, the convergence of hardware and AI will lead to sophisticated, seamless experiences far beyond current capabilities.

AI-Enabled Internal and External Transformation

AI is already driving transformation both internally and externally. Internally, it streamlines processes, enhances employee experiences, and significantly boosts productivity. In customer service operations, for example, GenAI has driven productivity improvements of 15% to 30%, with some companies targeting up to 80% efficiency gains.

Externally, AI is reshaping customer interactions, making them more personalized, efficient, and intuitive. Virtual co-pilots assist customers by answering inquiries, processing returns, and curating tailored offers—freeing human employees to focus on complex issues that require nuanced decision-making.

Linking Operational Efficiency to Customer Experience

Leading organizations are demonstrating how AI-driven efficiencies translate into enhanced CX.

• Amazon: The company’s expanding fleet of warehouse robots optimizes storage, picking, and packing operations. AI-driven quality control improves defect detection, while humans take on supervisory and maintenance roles. These innovations enable faster, more flexible delivery, with Amazon reporting that in March 2024, 60% of Prime orders in the top 60 U.S. metropolitan areas were delivered on the same or next day. Amazon also aims to cut peak-season cost-to-serve by 25% with its next-generation warehouses.
• Klarna: The global “buy now, pay later” leader launched an AI customer service assistant powered by OpenAI in early 2024. Within its first month, the assistant handled a workload equivalent to 700 full-time agents. Customer satisfaction remained comparable to human-led interactions, while response accuracy reduced repeat inquiries by 25%, and resolution times dropped from 11 minutes to under 2 minutes. Klarna projects $40 million in additional 2024 profits from these AI implementations.

Despite these gains, companies must raise the bar even further to fully capitalize on AI’s potential. The convergence of next-generation hardware with AI-driven automation presents an unprecedented opportunity to redefine customer engagement.

From App-Driven Experiences to Autonomous Agents

At Dreamforce 2024, Salesforce CEO Marc Benioff highlighted that service employees waste over 40% of their time on repetitive, low-value tasks. Similarly, customers face friction in making significant purchases or planning events. Google research indicates that travelers may engage in over 700 digital touchpoints when planning a trip—a fragmented and often frustrating experience.

Imagine instead a network of proprietary and third-party agents seamlessly executing customer missions—such as purchasing a car or planning a vacation—without requiring constant user input. These AI agents could:

• Access personal preferences to tailor recommendations
• Automate complex research, comparisons, and bookings
• Adapt in real time to changing conditions, such as traffic or weather
• Manage recurring tasks like home maintenance, shopping, and fitness planning

This “agentic AI” model represents a shift from passive app-based assistance to proactive, intelligent automation, significantly reducing user effort while enhancing outcomes.

Convergence of AI and Hardware: A New Paradigm

The next evolution in AI-driven CX will be multimodal AI agents integrated into everyday devices. Rather than relying on screen-based interactions, customers will engage with AI via voice commands, augmented reality, and even biometric inputs. This transformation will:

• Reduce dependency on traditional apps and screens
• Enable seamless, context-aware AI assistance
• Improve accessibility and ease of use across various settings

For example, Meta and Ray-Ban’s smart glasses demonstrate how AI-powered wearables can enrich daily life. These glasses offer real-time image recognition, live streaming, music playback, and foreign language translation—all without requiring a smartphone. Meanwhile, OpenAI’s collaboration with former Apple designer Jony Ive is expected to produce similarly immersive AI-driven experiences.

Strategic Actions for Businesses

Companies must move beyond experimentation and take concrete steps to integrate AI into their CX strategies. Following the Deploy-Reshape-Invent framework, businesses should:

1. Design for Missions, Not Just Journeys
   • Transition from linear customer journeys to holistic customer missions.
   • Build AI-driven vertical integrations that anticipate and fulfill user needs proactively.
2. Adopt New CX and Operational Metrics
   • Go beyond traditional satisfaction scores to incorporate cost-to-serve metrics.
   • Measure direct correlations between efficiency gains, CX improvements, and financial performance.
3. Re-Evaluate Investment Priorities
   • Prioritize AI investments that bridge operational enhancements with CX transformation.
   • Establish clear short- and long-term ROI projections to justify and sustain innovation efforts.
4. Drive Organizational Convergence
   • Integrate AI capabilities across teams and functions to maximize impact.
   • Launch deep proof-of-concept initiatives to identify scalable, high-value AI applications.

The Future: A Convergence of Innovation and Value Creation

The intersection of AI, next-generation hardware, and autonomous agents presents a transformative opportunity for businesses. Companies that strategically embrace this convergence will unlock a new standard of operational excellence, customer satisfaction, and financial performance. As AI seamlessly integrates into daily life, the familiar link between efficiency and CX will evolve into a powerful engine of innovation and long-term value creation.

By Shannan Hearne, Tectonic Director of Marketing Operations