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In the evolving landscape of artificial intelligence, the concept of Agentic AI  is rapidly gaining traction—and for good reason. As highlighted by NTT DATA’s Global GenAI Report,  this next-generation technology isn’t just about automating repetitive tasks or providing basic responses. It’s about empowering organizations with AI systems that operate autonomously, think critically, and execute tasks as effectively as human teammates.  Rethinking Technical Support with Agentic AI At Ascendo AI, we believe this evolution is particularly transformative for technical customer support. Let’s explore why agentic AI represents a seismic shift—and how AI agents and teammates can redefine support strategies for organizations aiming to meet rising customer expectations.  The Promise of Agentic AI   NTT DATA’s report  underscores both the potential and the challenges of generative AI (GenAI). With 97% of CEOs  expecting material impact but only 43%  satisfied with current solutions, the demand for innovation is clear. Agentic AI addresses this gap by introducing systems that go beyond reactive, rule-based automation. Instead, these AI agents:  Make real-time decisions using advanced analytics.  Execute complex workflows autonomously.  Act as “thinking” entities that collaborate with human teams to drive meaningful outcomes.  This capability aligns with today’s industry needs for efficiency , automation , and enhanced customer experiences , making agentic AI a game-changer for sectors like healthcare, insurance, and technical support.    AI Agents in Technical Support: A Game-Changer   Imagine a world where your AI teammate doesn’t just answer FAQs but takes on nuanced, multi-step support tasks with precision. At Ascendo AI, we’re seeing this vision materialize in two core roles:  AI Agents for Workflow Execution   Agentic AI empowers support teams by automating time-consuming tasks, such as identifying issues in product logs, updating records, or managing case escalations. By taking on these responsibilities, AI agents free up human agents to focus on strategic problem-solving, ensuring faster resolution times and happier customers.  AI Teammates for Collaborative Decision-Making   Today’s technical support challenges demand more than just task execution—they require adaptive thinking. AI teammates can analyze complex datasets, suggest solutions, and even autonomously implement fixes in low-risk scenarios. Think of them as tireless collaborators that enhance your team’s productivity and capability.  Transforming Technical Support Operations   Adopting agentic AI isn’t about replacing people—it’s about empowering them. Here are three immediate ways it can enhance support operations:  Increased Efficiency:  By automating repetitive tasks, support teams can process tickets faster without sacrificing quality.  Reduced Downtime:  Real-time decision-making allows AI agents to proactively address issues, reducing downtime for customers.  Enhanced Customer Experience:  Faster resolutions and personalized interactions lead to more satisfied customers who trust your brand.  These benefits reflect the industry-wide need for scalable, intelligent systems that adapt to evolving demands.    Building a Future with AI Teammates   As NTT DATA’s report suggests, successful adoption of agentic AI requires preparation, integration, and collaboration. At Ascendo AI, we’re committed to partnering with organizations to navigate this journey. From ensuring data readiness to aligning AI capabilities with business goals, we believe in a collaborative approach that prioritizes trust and reliability.  But this shift isn’t just about technology—it’s about mindset. It’s about seeing AI not as a tool, but as a teammate. By fostering a culture that embraces AI-driven innovation, businesses can unlock the full potential of agentic systems and stay ahead in an increasingly competitive market.    Looking Ahead   Agentic AI is still in its early stages, but its impact is already clear. As organizations define use cases and identify partners to bring this technology to life, the question isn’t  if  agentic AI will transform customer support—it’s  when .  At Ascendo AI, we’re proud to be at the forefront of this revolution. Whether you’re exploring AI for the first time or looking to optimize existing solutions, our intelligent, innovative platform is here to help. Together, we can reimagine what’s possible in technical support and build a future where AI teammates and human agents work side by side to deliver exceptional results.  Let’s redefine customer support—one intelligent agent at a time. Learn More:  Slow and Steady: Why AI in Technical Support is Poised for Transformation in 2025 Bridging the AI Knowledge Gap: Transforming Support Strategies with AI Teammates

As we enter 2025, the transformative role of AI in field service has never been clearer. Sarah Nicastro’s insightful article, " What Do Field Technicians Want from Technology? " , spotlights a workforce caught between the promise of technology and the challenges of adaptation. Her analysis of the Service Council’s “Voice of the Field Service Engineer” survey is a must-read for anyone seeking to understand the evolving dynamics of this critical industry. At Ascendo AI, we see these insights as a call to action—a guidepost for how AI can empower both technicians and organizations to thrive.  The Year Ahead: How AI Agents Are Shaping Field Service Excellence in 2025  The Balancing Act: Automation vs. Creativity   Nicastro’s article raises an essential question: Is automation making field service work too mundane? It’s a sentiment we’ve heard echoed in many industries where repetitive tasks risk overshadowing the creative, problem-solving aspects that skilled professionals value most. The survey’s findings —93% of technicians say technology boosts productivity, yet over half their day is consumed by paperwork—underline the need for smarter, more targeted solutions.  At Ascendo AI, we believe the answer lies in collaboration between human expertise and AI teammates. Our AI Agents are designed not to replace creativity but to amplify it. By automating the repetitive (like data entry and parts inventory management), we free up technicians to focus on what they do best: solving complex problems and delivering outstanding service.  AI Agents: The Teammates You Didn’t Know You Needed   Imagine this: A technician on-site encounters a challenging issue. Instead of sifting through lengthy manuals or making costly support calls, they turn to an AI teammate powered by Ascendo AI. Within seconds, the AI Agent offers:  Live troubleshooting steps using AI-based tools , cutting diagnosis time in half.  Augmented Reality overlays , showing exactly where to focus repairs.  Real-time parts inventory visibility , ensuring no time is wasted hunting for components.  These aren’t futuristic dreams—they’re today’s capabilities, ready to meet the needs Nicastro highlighted in her analysis. By integrating these solutions, we’re not just improving efficiency; we’re reshaping how field service teams operate.  The Future of Field Service is Human-Centric   It’s worth noting Nicastro’s emphasis on what technicians value most: empowerment, innovation, and safety. These priorities align perfectly with what Ascendo AI aims to deliver.  Empowerment:  AI Agents eliminate tedious tasks, enabling technicians to focus on high-value, creative work.  Innovation:  Our platform encourages continuous learning, keeping teams at the cutting edge of technology.  Safety:  From real-time hazard alerts to ergonomic task management, AI ensures technicians stay safe in the field.  Yet, as Nicastro wisely cautions, technology must be deployed thoughtfully. Over-automation risks alienating workers, particularly older technicians who may resist rigid, one-size-fits-all solutions. That’s why Ascendo AI champions a collaborative deployment model, where AI tools are co-created with end users, ensuring they feel like partners in the process.  2025 and Beyond: The Road Ahead   As we look to the future, one thing is clear: The success of field service organizations will depend on their ability to harness AI intelligently and empathetically. The trends Nicastro highlights—from a younger, tech-savvy workforce to the growing demand for AR and video support—signal a new era of opportunity. But seizing it requires the right approach.  At Ascendo AI, we’re not just building tools; we’re fostering relationships between AI and humans that make work better for everyone involved. Our AI Agents are more than algorithms; they’re teammates who understand the pressures, challenges, and rewards of field service work.  So, what does 2025 hold for field service? If organizations embrace AI as an ally—a partner that empowers rather than replaces—the possibilities are endless. The right balance of automation and creativity can transform mundane tasks into moments of innovation and redefine what’s possible in technical support.  Let’s explore that future together. At Ascendo AI, we’re ready to help you lead the way.  Learn More: AI Agents, AI Teammates, and Transformation: Insights for 2025 and Beyond Revolutionizing Field Service: The Role of AI in Empowering Technicians and Transforming Customer Support

Innovation in field service isn’t about grand gestures or sweeping transformations; it’s about focusing on the details that create meaningful change. Lauren Slater’s insightful article, Small Steps, Big Shifts: Driving Innovation through Disruption , offers a masterclass on how organizations like TOMRA and ACCO are achieving this balance . At Ascendo AI, we couldn’t agree more with her emphasis on blending high-quality data, frontline engagement, and collaborative change management to drive success. In fact, we see these elements as cornerstones for integrating AI-driven solutions into field service strategies.  Disruption, Data, and the Future of Field Service: The Role of AI Teammates Let’s explore how AI Agents and AI Teammates can revolutionize these foundational aspects of field service, creating ripple effects across efficiency, automation, and customer experience.  Data Quality: The Launchpad for Success   Slater’s spotlight on TOMRA and ACCO underscores a simple truth: data is only as valuable as its quality. For AI to thrive in field service, it needs to start with clean, actionable data. AI Agents—like the ones powered by Ascendo AI’s platform—are designed to analyze, organize, and interpret data at scale, ensuring that field teams have access to precise insights when they need them most.  Imagine an AI teammate that:  Identifies patterns in first-time fix rates.  Predicts the likelihood of service delays.  Highlights training gaps for technicians based on real-time performance metrics.  This kind of intelligent data processing doesn’t just improve service outcomes; it empowers teams to make smarter, faster decisions.  Empowering Frontline Teams Through AI   Slater’s research points to a key bottleneck in scaling innovation: the disconnect between frontline workers and organizational change. At Ascendo AI, we believe AI Teammates can bridge this gap. By acting as collaborative partners rather than standalone tools, AI Teammates:  Assist technicians in the field with on-demand diagnostics and repair guides.  Capture and integrate feedback from the frontline to refine processes and improve future recommendations.  Offer career development insights by tracking performance metrics and suggesting tailored upskilling opportunities.  TOMRA’s approach to involving technicians early in tech rollouts mirrors our philosophy: innovation works best when it’s driven from the ground up. AI Teammates can amplify this collaboration, making the adoption of new tools seamless and effective.  Simplifying Complexity with AI Tools   As Christine LaVoi from IFS aptly noted, technicians aren’t flipping through manuals anymore. They’re turning to solutions that prioritize speed and accuracy. That’s where AI Agents shine. By providing simplified, context-rich insights, they eliminate noise and allow field service professionals to focus on what they do best: solving customer challenges.  For example, an AI Agent might:  Deliver step-by-step troubleshooting based on live data from connected devices.  Automate routine tasks like scheduling, inventory checks, or report generation.  Adapt to each technician’s workflow, offering customized recommendations that enhance efficiency.  This isn’t just about saving time; it’s about creating space for technicians to deliver exceptional customer experiences.  Stay Focused, Stay Transformative   Michael Potts’ advice to avoid chasing every new trend resonates deeply. AI Agents and Teammates are most effective when they align with core business objectives, addressing real customer needs without unnecessary complexity. At Ascendo AI, we’re committed to designing solutions that focus on delivering measurable impact, ensuring that every step forward is both deliberate and transformative.  Transforming Field Service, One Step at a Time   Disruption doesn’t always have to be seismic. As Slater’s article demonstrates, the combination of small, focused changes can yield big shifts. With AI Agents and Teammates in the mix, organizations have an unprecedented opportunity to enhance data quality, empower their teams, and simplify complexity—all while staying aligned with customer needs.  At Ascendo AI, we’re here to help you navigate this journey. Whether you’re looking to explore the potential of AI in your field service operations or ready to integrate intelligent agents into your workflows, we’re excited to collaborate and build the future together. Let’s start small and think big because that’s how transformation happens.  Learn More: The Year Ahead: How AI Agents Are Shaping Field Service Excellence in 2025 Revolutionizing Field Service: The Role of AI in Empowering Technicians and Transforming Customer Support

As we step into 2025, the role of AI in customer support is not just about keeping pace with change; it’s about reshaping the very essence of how businesses engage with customers. Rekha Srivatsan, in her insightful article " The Future of Customer Service: What You Need To Know for 2025 ,"  highlights pivotal trends that are transforming the landscape of customer service. Here at Ascendo AI, we see these trends as a call to action for organizations to embrace AI as a true teammate, not just a tool. The Future of AI in Technical Support: Big Ideas for 2025   AI Agents: More Than Just Automation   Imagine an AI agent that doesn’t just respond to customer queries but proactively identifies and resolves issues before they arise. This is no longer a futuristic dream—it’s today’s reality. Autonomous AI agents, like those powered by platforms such as Ascendo AI, are redefining efficiency and personalization in technical support. These agents don’t simply work 24/7; they learn and adapt, becoming more precise and intuitive with each interaction. The result? Happier customers, higher loyalty, and a tangible boost in efficiency.  Srivatsan aptly notes that companies hesitant to integrate AI risk falling behind. At Ascendo AI, we’ve observed firsthand how businesses leveraging trusted and unified AI solutions can achieve scalable, secure, and cost-effective support strategies. These AI agents are not here to replace human ingenuity but to amplify it, serving as reliable teammates to support staff.  Field Service: Elevating Frontline Efficiency   Field service workers are often the unsung heroes of customer support, bridging the gap between digital and physical interactions. As Srivatsan’s article highlights, augmented reality (AR) tools and predictive AI are game changers in this domain. Platforms like ours at Ascendo AI empower these frontline workers by:  Simplifying Complex Tasks : AR capabilities integrated into mobile apps streamline workflows, enabling technicians to visualize and measure spaces in real-time.  Proactive Problem-Solving : Predictive maintenance ensures devices are serviced before issues escalate, saving time and resources.  Enhancing Self-Service Options : With 61% of customers preferring self-service for simple issues, AI-driven systems free up technicians to focus on higher-value tasks.  By integrating AI into everyday tools, field service teams become more proactive, productive, and aligned with customer needs. This alignment is critical in addressing rising workloads and maintaining job satisfaction among frontline workers.  AI as a Revenue Driver   One of the most exciting shifts in 2025 is the reimagining of customer support as a revenue generator. Srivatsan’s observation that 85% of decision-makers now view service as a growth driver underscores a pivotal shift. AI-powered insights provide a continuous feedback loop between sales, service, and marketing teams, fostering collaboration and enhancing customer lifetime value.  At Ascendo AI, we see this convergence of metrics as an opportunity to unify goals across departments. By providing AI-driven recommendations tailored to customer preferences, businesses can seamlessly integrate cross-selling opportunities into support interactions. This holistic view of the customer's journey transforms every touchpoint into a chance to build deeper relationships and drive growth.  Preparing for the Future   The insights from Srivatsan’s article resonate deeply with our mission at Ascendo AI. To thrive in 2025 and beyond, businesses must adopt an AI-first mindset, combining people, technology, and processes to deliver faster, smarter, and more personalized support. Here’s how:  Invest in Unified Platforms : Consolidate technology to enable seamless data sharing and collaboration across teams.  Empower Teams with AI Teammates : Equip staff with AI tools that enhance decision-making, reduce manual workloads, and anticipate customer needs.  Embrace Proactivity : Leverage AI for predictive assistance, ensuring issues are addressed before customers even notice them.  Why It Matters   The future of customer support isn’t just about keeping customers happy—it’s about redefining what’s possible. At Ascendo AI, we believe in the transformative power of AI to elevate both efficiency and experience. By 2025, businesses that see AI as a strategic partner will lead the way in building stronger customer relationships, retaining talent, and driving sustained growth.  Ready to explore how AI can transform your support strategy? Let’s collaborate to make 2025 your most innovative year yet.  Learn More: The Year Ahead: How AI Agents Are Shaping Field Service Excellence in 2025 Why 2025 Will Redefine Technical Support: The Role of AI Teammates in Driving Efficiency

In the evolving landscape of artificial intelligence, multimodal AI is emerging as a pivotal innovation, transforming how businesses manage and enhance customer support experiences. As highlighted by Lutz Finger in a recent Forbes article , this technology integrates diverse data types—text, images, audio, and more—to deliver comprehensive insights. By 2025, multimodal AI is expected to drive significant advancements across industries, from healthcare to eCommerce.  2025 Vision: The Role of Multimodal and Agentic AI in Technical Support At Ascendo AI, we recognize the transformative potential of multimodal AI, particularly in technical support. Our agentic AI platform leverages these advancements to empower support teams with intelligent, context-aware assistance. Here’s how multimodal AI and agentic AI are shaping the future of customer service.  Multimodal AI: A Comprehensive Approach to Data Interpretation   Lutz Finger explains that multimodal AI systems integrate multiple data sources to create a unified understanding of complex problems. This approach allows AI to interpret:  Text-based customer tickets  that describe issues.  Log files and diagnostic reports  that provide technical data.  Screenshots and videos  that offer visual context.  While traditional support systems handle these data points in isolation, multimodal AI synthesizes them, delivering deeper insights and faster resolutions. By connecting disparate inputs, it enables support teams to respond with precision and personalized solutions.  From Automation to Collaboration: AI Agents as Intelligent Teammates   Multimodal AI does more than automate repetitive tasks. As Finger emphasizes, it excels in discovery and relevance, not just correlation. This aligns with Ascendo AI’s vision of agentic AI platforms , where AI agents function as collaborative teammates, enhancing human decision-making:  Advanced Contextual Understanding : AI agents interpret text, logs, screenshots, and historical data to provide actionable insights, helping resolve complex support cases.  Proactive Assistance : By analyzing multimodal data, AI agents offer proactive recommendations, identifying potential issues and suggesting solutions before problems escalate.  Learning and Personalization : Like personalized eCommerce recommendations, AI agents continuously improve by learning from previous cases, ensuring more accurate and relevant responses over time.  Practical Applications: Enhancing Efficiency and Customer Satisfaction   Consider a scenario where a customer reports intermittent connectivity issues. A traditional support system might provide general troubleshooting steps based on keywords. In contrast, a multimodal AI platform:  Analyzes the text of the support ticket to understand the reported issue.  Reviews screenshots for visible error messages.  Examines device logs to identify patterns in connectivity failures.  Cross-references similar cases to suggest tailored solutions.  This comprehensive analysis leads to faster case resolution, reduced escalations, and improved customer satisfaction.  AI as a Collaborative Partner   AI’s role in customer support is evolving from simple automation to intelligent collaboration. Multimodal, agentic AI empowers support teams by augmenting their capabilities, enabling them to deliver more responsive, context-aware service. Companies that embrace this technology will be better equipped to meet the rising expectations of modern customers.  Lutz Finger’s insights remind us that AI’s true potential lies in enhancing human expertise. At Ascendo AI, we are committed to driving this evolution by integrating multimodal AI into our platform. We invite you to explore how AI agents can transform your support strategy, improving efficiency, personalization, and customer experience.  Reach out to learn how we can help shape the future of AI-driven support together.  Learn More: The Year Ahead: How AI Agents Are Shaping Field Service Excellence in 2025 Why 2025 Will Redefine Technical Support: The Role of AI Teammates in Driving Efficiency

In the fast-evolving world of Technical Support, the promise of AI shines brightly. From self-service solutions to real-time agent assistance, AI tools are transforming the way businesses interact with their customers. However, as Adrian Swinscoe aptly highlights in his recent article, " Are Humans the Missing Link in Your AI Strategy? " , the journey isn’t just about machines becoming smarter—it’s about how humans and AI collaborate to deliver the best outcomes.  Unlocking the Power of AI-Human Collaboration in Technical Support At Ascendo AI, we couldn’t agree more. Our approach to agentic AI—AI that acts as a teammate rather than a replacement—aligns perfectly with Swinscoe’s emphasis on the importance of the human element in AI strategies. Let’s dive into what this means for technical support and field service teams and how businesses can leverage both artificial intelligence and agent intelligence to unlock new levels of efficiency and customer satisfaction.  AI Agents as Teammates, Not Replacements   The rise of generative AI has ushered in a new era for technical support teams. These tools can read customer inquiries, analyze them in real-time, and suggest actionable solutions. Yet, as Swinscoe points out, the potential for AI to "hallucinate" or misinterpret complex issues necessitates a Human-in-the-Loop  (HITL) approach. This collaboration allows AI agents to learn from human expertise while ensuring reliability in customer interactions.  At Ascendo AI, our platform is designed to empower technical support agents with AI teammates that proactively assist in diagnosing issues, suggesting fixes, and even predicting potential problems before they arise. This isn’t about replacing human roles but enhancing their capabilities. By enabling agents to focus on nuanced, high-value tasks, AI teammates drive both efficiency and deeper customer engagement.  The Chatbot Challenge and the Emotional Gap   Swinscoe’s insights on chatbots are particularly striking. Despite significant investments, customer satisfaction with chatbots has steadily declined—falling from 35% in 2017 to just 21% in 2022. Why? The lack of personalization, emotional intelligence, and seamless escalation paths frustrate customers who expect more from modern technology.  This is where agentic AI can redefine the narrative. By integrating contextual understanding and multimodal AI capabilities, chatbots and virtual agents can shift from transactional tools to empathetic problem-solvers. Imagine a chatbot that not only recognizes the urgency in a customer’s tone but also seamlessly hands off complex issues to a human agent, complete with all the contextual data needed for a smooth transition. That’s the kind of intelligent, collaborative support Ascendo AI strives to deliver.  Why Employee Expertise Matters   One of Swinscoe’s most compelling points is the underutilization of customer service agents in the design and refinement of AI systems. Who better to guide chatbot conversations and troubleshoot design flaws than the very people who interact with customers daily? Yet, as Swinscoe notes, many organizations fail to tap into this well of insight.  At Ascendo AI, we view customer service teams as co-creators in the AI journey. Through Voice of the Employee  (VoE) initiatives, we actively involve agents in shaping how our AI tools operate. From refining troubleshooting workflows to designing AI-powered knowledge bases, their feedback ensures our platform remains intuitive, effective, and aligned with real-world needs. After all, the best AI is built by humans, for humans.  Bridging the AI-Human Divide   The future of Technical Support isn’t about choosing between AI and human intelligence. It’s about blending the two seamlessly to create a support ecosystem that’s efficient, empathetic, and ever-evolving. At Ascendo AI, we believe that agentic AI—AI designed to work alongside humans as proactive teammates—is the key to achieving this vision.  Swinscoe’s call to action is clear: leverage the expertise of your people, embrace collaboration, and design AI systems with both emotional and contextual intelligence. We’re proud to be at the forefront of this movement, helping businesses harness the full potential of AI to transform technical support and field service operations.  So, here’s our question to you: How are you involving your teams in shaping the future of AI in your organization?    Let’s start a conversation. Together, we can create solutions that don’t just work but truly connect.  Learn More: 2025 Vision: The Role of Multimodal and Agentic AI in Technical Support Scaling Technical Support Smarter: Anjuna Security's AI-Driven Success Story

As the technology services sector embarks on what promises to be a transformative year, businesses are navigating a delicate recovery from one of the longest downturns in recent memory. Peter Bendor-Samuel’s recent article in Forbes , " The Future of Technology Services: Key Trends for 2025 " , highlights pivotal shifts in the industry—trends that resonate deeply with Ascendo AI’s vision for intelligent support solutions.  The Evolution of Service: How AI Agents Are Shaping the Future of Support Bendor-Samuel points to a renewed focus on modernization, driven by a clear demand for measurable outcomes rather than piecemeal upgrades. Companies are moving away from feature-chasing and toward building scalable, sustainable platforms that create lasting business value. This shift isn’t just about technology—it’s about alignment between operational goals and technological investments. The same principles apply to technical support and field service, where AI-driven automation and predictive capabilities  are poised to deliver transformational impact.  AI Agents: The Strategic Modernization of Support   When we talk about modernization in support services, we’re not discussing simple chatbots or scripted responses. At Ascendo AI, we envision a future where  AI Agents  act as proactive teammates  alongside human technicians. These AI teammates bring context, agility, and predictive insights to the forefront of technical support, offering three key advantages that align with current industry needs:  Proactive Troubleshooting and Predictive Assistance : Bendor-Samuel underscores that enterprises now prioritize integrated solutions with clear returns on investment. AI agents embody this shift by detecting potential issues before they escalate. They use real-time data and predictive analytics to diagnose root causes, reducing downtime and improving resolution times—a boon for both efficiency and customer satisfaction.  Seamless Collaboration with Human Teams : Unlike traditional automation that replaces human interaction, AI-driven agents from Ascendo AI work collaboratively, augmenting human expertise rather than replacing it. By understanding context and maintaining continuity across customer interactions, they empower technical support teams to deliver personalized, efficient experiences. This reflects the broader industry demand for holistic, end-to-end service modernization.  Data-Driven Insights for Strategic Decisions : The rise of Global Capability Centers (GCCs), highlighted by Bendor-Samuel, illustrates how businesses are reclaiming control over their operations. AI Agents provide the intelligence backbone for these efforts, transforming service data into actionable insights that optimize workflows, enhance resource allocation, and drive continuous improvement.  Modernizing Technical Support for Tomorrow’s Needs   Technical support is no longer just about resolving issues after they occur. It’s about anticipating problems before they disrupt operations , delivering seamless resolutions, and continually enhancing the overall support experience. AI-powered technical support solutions , like those from Ascendo AI, excel at contextual understanding, automating repetitive tasks, and providing real-time recommendations to technicians—freeing human experts to tackle more complex challenges and strategic initiatives.  By integrating AI agents into technical support workflows, companies can:  Reduce Mean Time to Resolution (MTTR)  by automating diagnostics and delivering proactive recommendations.  Enhance First Call Resolution (FCR) rates  with contextual insights and guided assistance.  Improve Customer Experience (CX)  through faster, more personalized service that adapts to evolving needs.  This modernization of technical support aligns perfectly with the industry’s broader shift toward data-driven decision-making and holistic, scalable solutions.  Meeting Customers Where They Are: A New Paradigm   The uneven recovery across industries and regions presents both challenges and opportunities. While North America leans into modernization, Europe prioritizes cost-saving strategies. As technology partners tailor solutions to these divergent needs, AI-driven support platforms must remain adaptable. Ascendo AI’s agentic AI  is built with flexibility in mind, scaling to fit unique operational demands while delivering consistent, measurable outcomes.  The future Bendor-Samuel describes—one defined by value-driven investment and strategic partnerships—is precisely the space where AI agents thrive. Intelligent automation, contextual understanding, and real-time decision-making aren’t just buzzwords; they’re the tools that drive competitive advantage in today’s service landscape.  Why AI Agents Matter More Than Ever   Modernizing support isn’t simply about keeping up with trends. It’s about meeting evolving customer expectations and staying ahead of the next wave of disruptions. AI teammates do more than handle repetitive tasks—they proactively enhance efficiency, improve accuracy, and free human experts to focus on higher-value problem-solving.  In Bendor-Samuel’s words, the road ahead requires resilience, adaptability, and relentless focus on value creation. At Ascendo AI, we believe AI agents are the partners that help businesses travel that road—unlocking hidden potential, turning insights into action, and transforming support from a reactive necessity into a proactive advantage.  The evolution of technology services is well underway. Are your support strategies keeping pace?  Explore how Ascendo AI can help you modernize your technical support with AI-driven efficiency and intelligence.  Learn More: 10 Game-Changing Trends in Field Service—and How AI Teammates are Leading the Charge The Year Ahead: How AI Agents Are Shaping Field Service Excellence in 2025

Businesses these days receive hundreds and even thousands of customer queries daily. For any customer service representative, it becomes tremendously difficult to keep track of these issues, specifically because of the three Vs Volume Velocity and Variety With inconsistent similarities between large amounts of incoming data along with the frequency of product updates, it adds exponential complexity to the process of unearthing trends in the data. This data can be created from various data sources including customer-created tickets, service requests, bots, customer reviews, case objects from different CRMs, help articles, or even FAQs. While these datasets share the same ground of belonging to customer interactions , they all can have extreme differences in terms of unearthing actual actions to be derived from them. At Ascendo, we call these “Interactions”. What is common across these interactions is that they deal with symptoms/problems/ that a customer needs. Each of them needs an understanding of what the “ root cause ” of the request is. Then the root cause should be mapped to the relevant solution/knowledge to surface it back to the customer. At Ascendo we believe in Resolution instead of Deflection Resolution instead of just opening a ticket Resolution before Escalation Ascendo takes you on a journey to find out what you have been missing! For very raw data, Ascendo generates information, which in turn is converted to knowledge. This knowledge comes in the form of problems, symptoms, root causes, and solutions. And this knowledge comes to you in the simplest of forms. All you have to do is swing the magic wand and get all the insights that can make your experience with your end customers fantastic. Download the full whitepaper to read more on this...

“It takes a village to raise a child” is an African proverb that means an entire community of people must interact with children for those children to grow in a safe and healthy environment. (Source: Wikipedia). This proverb is not just true for raising a kid but also applies in the business context to grow any organization in a meaningful way. Customer Service is no different. It takes various stakeholders to work together to make their products and offerings service-ready and service capable. Ascendo has been razor sharp focused on the customer support area and is continuously getting enhanced to understand the unique needs of the various stakeholders and address their challenges. Let us take a look at the various stakeholders and how they think about their functions and how they are making their customer journeys into success stories. Support Delivery (Agents): Support teams want quick mechanisms to have their customers get self-help first. With improved technology bandwidth, a good number of customers first perform either a search or ask a chatbot to get the answers. Ascendo through its contextualization and correlation engines combined with its self-learning capabilities immediately identifies the context and the intent behind the search queries and chatbot questions and finds solutions from the in-depth knowledge it has garnered from within the support organization. Because of this, the “self-help” customers inherently feel better about appropriate or relevant solutions being suggested. The solutions become more meaningful. Support teams want to seamlessly get agents to help their customers when self-help may not be preferred or sufficient. Ascendo has the knack to identify if end customers require actual live help with the agents. Ascendo can automatically offer and transition the customer to get live help from one of the agents. Support teams want to make sure agents are getting the needed help to solve the issues. Ascendo helps the agents so they exactly know if the previously tried solutions did (or did not) work. Ascendo combines the “context” behind the customer questions and the tried solutions to further recommend better solutions to the agent. In Agent Assist mode, Ascendo looks into prior cases of similar nature and additional knowledge sources that are more reserved for internal audiences within the company and provides recommendations to the agents. This enables providing help and suggestions even for one-off complex issues as the engine mimics similar behavior. Support teams want to make sure agents are onboarded fast and know the expert to connect with. Before the “remote” workforce model, many agents were collocated and had the luxury of “swinging” their chairs and talking to their colleagues to get help. There is an inherent challenge in that agent is “supposed to know who to go to for help”. With an increased remote workforce that has become a bit harder. Also, knowing the expert has become a unique trait of agents rather than corporate knowledge. Even in a colocation scenario, agents tend to ask their neighbor “hey, do you know the answer for this?” and not necessarily the true expert that might know the answer in the back of their hand. This is where Ascendo comes into help. Ascendo has a way to automatically identify the “experts” based on how prior similar issues are solved, how many, and how effective they were. Ascendo uses its own unique modeling technique to derive the expert by first understanding the context in which the question is being asked, knowing the intent, and quickly mapping the issues that were similar to being asked, and detecting the experts based on how well they solved the issues. Ascendo knows the difference between quantity and quality. The modeling technique uses customer satisfaction on the prior solutions to improve the ability to determine the expert. Support Leaders If you ask Support Leaders what keeps them up at night, it would be delivering a fantastic support experience at an optimized P&L. Depending on the type of company, onboarding a support engineer can take anywhere from 6 weeks to as much as 12 months. This does not even include initial shadow/review time spent on the new support engineers. Support Leaders not only about the cost of onboarding but also the opportunity cost of the time. Ascendo is proven to help in reducing the onboarding time due to its inherent nature of being an “experts in back pocket” model. Engineers can easily learn the solutions by querying within Ascendo and that reduces the time and the areas they need to look to provide solutions to customers. Another issue that Support Leaders grapple with is customer escalations. Once customer escalates, they do all they can including involving the best resources, being available for the customers, potentially offering new concessions, and other benefits to keep the customers happy. They are being forced to become reactive and counterintuitive to them wanting to be in charge and lead. They can rely on Ascendo on two fronts: Ascendo predicts potential escalations before they occur and Ascendo predicts the sentiment of the customer using hidden signals and communications from the customer users. Ascendo does this in real-time and alerts the support agents so they can pay even more close attention to the customer's problems. This type of model allows the customer leaders to switch their engagement with their customers from being reactive to proactive and they can regain their advantageous position of being in drive to realize the outcome – delightful customers. Support leaders are seeking to understand hidden trending issues before they become serious. Given the nature of the Ascendo modeling techniques, it can group or cluster incoming issues based on context, intent, and symptoms. No manual effort is needed from the support team to involve multiple team members to comb through the tickets to identify the top issues. Ascendo knows the top issues could change over time and constantly looks at them and provide the support leaders early guidance on the top issues. Knowing top issues also allows the Support Leaders to develop appropriate solutions: Do they need to make fundamental changes in the product? Do they need to train their engineers more? Do they need enrich their knowledge? The early alerts on top issues also allow the Support Leaders to focus their resources on the important things. They can assign fewer resources to focus on issues that matter most to their customers. Support Leaders can also empower their support delivery teams to increase self-service and auto resolution of many routines and/or high-volume customer questions. Instead of support agents needing to look at every issue, they can review Ascendo recommendations and use that to address their backlogs more effectively including auto-answering with possible solutions. The advantage is two-fold: Their customers get solutions quickly and Their agents' productivity increases. Field Engineers Field engineers/Field Techs come into play when the company makes hardware / electro-mechanical type of products or make complex products that require a field person or a professional engineer to work with them. Companies are always looking to reduce both the time and the number of trips the engineers spend to solve issues in the field. Customers also want a quick turnaround – they want the tech to come and complete the work quickly instead of needing to come multiple times. Ascendo can provide a game plan using its arsenal of solutions: It provides the optimum predictions on the root cause The area of fault and Recommendation on parts, if such is needed. Field engineers can use this game plan and are much better prepared before they even visit the customer. They have a fair knowledge of what the problem might be and also can carry the parts. The diagnostics become simpler and no more need to come back again for a part. The entire resolution could be done in one visit and in less time. Such savings in labor and travel is significant. Their customers are also much happier as they get their systems back up and running optimally in less time. This win-win is possible because of Ascendo’s exhaustive self-learning capabilities. Logistics Support teams that need to have spare parts face the unique challenge of needing to stock spare parts in one or more locations (depots) to satisfy support contract commitments they have with their customers. Depending on the mission-critical nature of their products, they may be offering various service levels such as 4-hour replacement, 8-hour replacement, or Next Business Day (NBD). Given their customers are geographically disbursed, support teams may have to stock spare parts in more than one distribution center and depots. Global companies, may also take into consideration specific country custom rules when deciding the location and quantity of their spare parts. Ascendo can use various information such as the field failure characteristics, customer install base growth trend, specific consumption pattern at depot-part level, and type of support contracts, and recommend the spare parts stocking requirements. Using Ascendo, the logistics team can optimize their spare plan in a much more effective way. Ascendo works in conjunction with the support teams' ERP system and the planners can use Ascendo recommendations to determine their reorder point (ROP) at the spare part-location level. Ascendo uses the prediction logic and provides customer SLA risk and the logistics team leaders can use that to take proactive actions. Furthermore, Ascendo can detect the change in install base movement and the change in the companies third part logistics team locations and provide proactive alerts for the logistics team to better plan their spare parts move as well as procurement. Support Operations Support Operation teams are a glue to connect people, processes, and technology to the needs of the various support delivery teams. They are incentivized to think about the future and create practical paths to connect the dots. Given the complex nature of the global service teams, Support Operations is looking to use AI/ML-based solutions that work with their existing deployed systems and artifacts and elevate them to the next level. Support Operations are leveraging solutions like Ascendo because Ascendo automatically learns them from their existing data. Ascendo has the needed connectors to work with their CRM systems and other knowledge/help articles and further enriches them in a meaningful way. The Setup process within Ascendo being straightforward helps with the quick implementation. The Support Operations team is also looking to deploy solutions that are value-based, and they are wanting to move away from user-based models to value-driven models. Given the way Ascendo can be easily consumed and deployed and the pricing model based on value realization, it makes it easier for the Support Operations team to try out and deploy Ascendo solutions. Summary Running a support organization is hard. The products are changing, customer demands are increasing, processes need to get adjusted, people are changing, and the need to constantly improve customer experience and support efficiency only keeps getting bigger and more important. It takes more than a village and Ascendo is right there to help with its fundamental self-learning capabilities, fine-tuned for customer support. Learn more, Tips To Stay In Continuous Touch With Customers Ways To Improve Customer Services With AI

What Is Employee Design Debt in Customer Support? Employee design debt in customer support refers to the accumulation of problems or inefficiencies in the way that customer support is structured or carried out that can lead to increased difficulty or burden for employees. This can occur when processes, systems, or tools are not well-designed or are not kept up-to-date, leading to frustration and decreased productivity for employees. Common Causes of Employee Design Debt Some common causes of employee design debt in customer support include: Lack of clear processes or guidelines for handling customer inquiries or complaints Outdated or cumbersome tools or systems for managing customer interactions Insufficient training or support for employees Poor communication or coordination among team members Lack of resources or support to handle customer needs effectively These issues will lead to a ticket backlog. To address employee design debt in customer support, it may be necessary to review and update processes, invest in new or improved tools and systems, provide additional training and support for employees, and ensure that there is clear communication and coordination within the team. It can also be helpful to seek feedback from employees to understand their experiences and identify areas where improvements can be made. What Can Modern Support Service Enterprises Do About Employee Design Debt? There are several steps that enterprises can take to address employee design debt in customer support: Identify the sources of employee design debt: It is important to understand the root causes of the problems that are leading to employee design debt. This may involve conducting surveys or interviews with employees to gather feedback and identify specific issues that need to be addressed. Review and update processes and systems: Outdated or inefficient processes and systems can contribute to employee design debt. Enterprises should review their current processes and systems to identify areas that can be improved or streamlined. Provide training and support for employees: Ensuring that employees have the necessary knowledge, skills, and resources to do their job effectively can help to reduce employee design debt. This may involve providing training or support for new tools and systems or offering ongoing support and guidance to help employees stay up-to-date with changing customer needs and expectations. Invest in new or improved tools and systems: If the current tools and systems being used by customer support teams are not effective or efficient, it may be necessary to invest in new or improved technology like self-service tools. This could include investing in new customer relationship management (CRM) systems or implementing automation tools to help streamline processes. Foster a culture of continuous improvement: Encouraging a culture of continuous improvement can help to prevent employee design debt from accumulating. This may involve encouraging employees to share ideas and suggestions for improving processes and systems and actively seeking feedback from employees to identify areas for improvement. Tools That Will Help With Employee Design Debt There are several items in any tool that can help enterprises address employee design debt in customer support: The Central Repository of Customer Interactions: Digital systems can help to centralize customer data and provide a single, comprehensive view of customer interactions. This can make it easier for customer support teams to access the information they need and respond to customer inquiries more efficiently. AI systems like Ascendo take it further to standardize all forms of customer interactions into time series data to analyze and prioritize based on escalations, sentiment, urgency, and many other parameters. It enables support teams to not just become proactive but to help the entire Enterprise become customer-centric. Collaboration and communication: Tools like chat and messaging platforms, video conferencing software, and project management software can help customer support teams stay connected and coordinated, reducing the risk of miscommunications and improving overall efficiency. Ascendo AI goes further to share who is the best person to contact for any particular type of issue. Knowledge Intelligence: Knowledge management systems can help to provide customer support teams with quick access to the information and resources they need to resolve customer issues. This can include everything from product documentation and troubleshooting guides to customer service policies and procedures. Knowledge intelligence goes a step further to assess customer interactions using artificial intelligence and share where gaps in knowledge are for employee productivity, quality, or efficiency. We at Ascendo, can show you how we do all this and more! Automation: Automation can help to streamline processes and reduce the burden on customer support teams by automating routine tasks or handling low-level inquiries. This can include bots or other automated response systems that can handle basic customer inquiries without the need for human intervention. Let intelligence from Ascendo spell out possible actions based on real-time data so your team can spend their time making and following through on decisions. Training and support resources: Providing access to training and support resources can help customer support teams stay up-to-date with new products, processes, and tools, and be better equipped to handle customer inquiries. This could include online training courses, in-person workshops, or ongoing support and guidance from team leaders or subject matter experts. Ascendo can help bring support intelligence, knowledge intelligence, and automation. Contact us to see a demo.