In August 2024, Movate spoke to NelsonHall about its in-house holistic framework, Movate Athena. Conversations revolved around the expectations and challenges of AI Integrations in the market. Specific use cases, existing deployments, and best practices in building commercial relationships around the AI reinvention model were part of the discussions. Movate has been actively integrating AI and GenAI into its tech stack, for example, the intelligent automation platform Movate Contelli, the CX transformation platform Movate Edison, and the business intelligence platform Movate Insights.
Movate Athena—a plug-and-play AI platform and data framework that helps enterprises build their complex AI capabilities. The team from Movate AI spoke about the different challenges organizations face when adopting GenAI, including the innate risks within LLMs related to bias and misinformation. The team shared design thinking guiding principles for effective AI deployment and governance. Various aspects that were covered during the discussion include on-field examples such as the GenAI-based chatbot and the co-creation of AI solutions for a global service desk for a multinational technology client.
Here are some of the vital areas we’ll cover:
- Movate’s dedicated AI unit
- Optimizing enterprise functions
- Jerky ride toward a bright AI future
- Circumventing challenges
- AI-enablement ecosystem
- Use cases: integrating GenAI
- Success stories: flexi outcome-based pricing
- Movate’s AI plans
A dedicated AI subsidiary
Movate launched its subsidiary, Movate AI Inc. Movate Athena—a modular plug-and-play AI plus data framework that helps enterprises craft AI strategies, build advanced AI capabilities, and transform them into AI-first and data-driven enterprises. Over the last couple of years, Movate has been actively integrating GenAI into its existing technology stack; examples include the intelligent automation platform Movate Contelli, the CX transformation platform Movate Edison, and the business intelligence platform Movate Insights.
Optimizing enterprise functions
The Movate Athena framework aims to optimize enterprise functions such as sales, marketing, HR, IT, and customer service. It seeks to support different internal and external stakeholders, such as customers, partners, and employees. Its ambition is to meaningfully empower experiences to drive CX and grow CLV (customer lifetime value), supported by digital product engineering resources and its transformation partners, such as Salesforce Einstein, Databricks, Uniphore, Conversica, NICE, and the rest.
A promising AI future
The future looks promising but not without bumps along the way.. Despite the keen interest of enterprises in GenAI capabilities over a year or more, on-field deployments at scale are likely to contend with challenges. Fragmented corporate structures and functional silos, legacy technology, low data quality and data overload, change management and people upskilling, and even digital fatigue are all commonplace in technology-led enterprise transformation. Common hurdles, such as cost, ROI, and innovation budgeting, have surfaced with the warpspeed of GenAI developments. The new potential roadblocks come from inherent risks within LLMs related to AI seed parameters such as discrimination and bias, misinformation and disinformation, privacy and trust, and overall governance and accountability to deliver responsible AI.
Navigating the challenges
Movate AI looks to circumvent these challenges through its design thinking principles. The guiding tenets (given below) for delivering enterprise-wide use cases cover the end-to-end processes.
Movate AI looks to organize the use case across its supporting industries and service lines. For example, automated code review and optimization and AI-powered code generation and completion for technology AI-guided software engineering; or CX agent assist in telecom customer churn prediction and prevention.
The company’s vision for AI enablement ecosystem in CX involves enablers such as user-centric design & personalization, personalized omnichannel CX continuity, context & proactive engagement at speed, multi-brand governance, asset creation, translation – localization & internationalization, digital (asynchronous) messaging, universal search feature, self-service and more. Movate AI will tap capabilities from its current suite of digital services, CX services, and Digital Engineering & Insights.
Use Cases: Integrating GenAI
While all of the aforementioned levers can be treated as the end targets of the Movate AI framework in CX, Movate integrates its existing GenAI-based tools into live client projects. Here are a few examples:
Amazon Connect: The team implemented Amazon Connect for global voice and chat, deploying five chatbots; launched GenAI for digital assets, automated customer interactions, The outcomes showed 98% accuracy in ticket routing, 95% in problem ticket creation, an 85% success rate in suggesting relevant knowledge/help articles and a 25% increase in engineers’ productivity.integrated Salesforce with Atlassian for improved data flow. They accelerated payment terminal business inquiries with a GenAI-based chatbot as part of the larger CX transformation for a top financial and payment solutions client, where it consolidated global teams and standardized support processes.
Smart case manager: For another client, Movate developed this solution offering smart routing, quality bots for feedback collection, and standardized CSAT tracking for all interactions. With this unified transformation approach, Movate delivered 20% deflection of issues and 50% automation of installation bookings, boosting back-office productivity by 30%. It enhanced self-service capabilities and unified portal access and reached a 20% reduction in TCO.
In IT services, for a technology company with ~160K employees and ~140K vendor partners worldwide, Movate implemented a global service desk where the team co-created AI solutions, provided operational insights, and recommended AI use cases. The team implemented proactive monitoring and self-healing, enhanced AI accuracy in ticket creation, routing, and knowledge recommendations for effective performance measurement, and tested and rated the developer copilot’s performance on multiple metrics.
The outcomes showed 98% accuracy in ticket routing, 95% in problem ticket creation, an 85% success rate in suggesting relevant knowledge/help articles and a 25% increase in engineers’ productivity.
Outcome-based pricing model
Movate AI looks to solve current client uncertainties around GenAI with its two-week service assessment to craft an AI/GenAI adoption roadmap and boasts approximately 400 reusable accelerator templates. There are fundamental questions (on AI implementations) as to what business goals organizations are willing to pay today and who owns the outcomes and the pay for the self-service content generated by AI. The standard answer to the former is productivity and operational enhancements, while the answer to the latter is yet to have more clarity.
A key highlight is the flexible outcome-based flexible pricing with the “skin-in-the-game” approach. Movate has spent time on these flexible pricing models for several years and has case studies, such as a U.S. telecom for which it created a hybrid delivery model leveraging automation, FTEs, and On-Demand experts to achieve a 25% TCO reduction with pay-per-resolution pricing. These convenient pricing models attuned to client’s business needs is a balanced approach that considers the interests of clients who have a well-defined outcome-based structures and executive buy-in.
Movate’s AI plans
Plans on the anvil include developing on the CX enablers and tapping the potential of client data for mining insights for continuous service improvements and revenue generation. Movate AI roadmaps include deploying the existing ~100 AI POCs and prototypes to integrate the framework and pricing model into a prospect’s sales process. From an operational standpoint, plans are afoot to create special agents and engineers with virtual assistants and copilots (as in the case of autonomous quality engineering) and expand to internal enterprise functions such as Finance and HR.