Generative AI for Tangible Impact: Deep Dive into ROI & Utility
In this article, we will break down how Generative AI can be implemented effectively in the modern enterprise, alongside a case study with real metrics.
Understanding the Real-World Impact of Generative AI
As 2023 winds down, the narrative surrounding #GenerativeAI (GenAI) has clearly evolved from speculative to strategic.
Seriously, how much more AI media generation and closed-GPTs can we endure before acknowledging the obvious elephant in the room?
With approximately 44% of professionals recognizing GenAI's critical role in their organizational future (ML Insider, 2023) — it's time to demystify the exact utility and return on investment (ROI) that LLMs and Conversational AI methodologies & technologies offer.
Decoding the Utility of Generative AI
While the overall sentiment has been that GenAI is only moderately important – only 10% of organizations launched LLM-based solutions into production (ML Insider, 2023).
The focus shifts to the trailblazers who have reaped tangible benefits.
For instance, the case of Tico, powered by Voiceflow, underscores the practical value of GenAI. Tico's integration into customer support workflows not only deflected thousands of tickets but also maintained high customer satisfaction, showcasing a direct correlation between GenAI deployment and enhanced Customer Operations.
The ROI of Implementing Effective AI
With Tico, we observed a deflection rate of 97% of potential tickets, indicating a substantial decrease in operational costs. The AI-driven support system accounted for only 4% of total support expenses while maintaining a 9.4 CSAT score, demonstrating an impressive ROI that GenAI can deliver when strategically deployed.
The cost-effectiveness of AI tools can no longer be overlooked.
From Theory to Practice: Building Your AI Agent
The journey from ideation to implementation of AI agents requires a meticulous approach. Here's a strategic outline for organizations looking to leverage GenAI for the first time:
Identify the Need: Pinpoint processes ripe for automation—be it customer queries or internal workflows. (ie. start with FAQs, then go to help center indexing then Knowledge Base x LLMs)
Choose the Right Platform: Ensure you are planning around complex org structures and processes. For us, opting for a robust platform like Voiceflow that offers customizability and scalability (bias aside) with conversational AI workflows.
Customize and Train: Tailor your AI agent with specific data relevant to your operations, and train it to handle real-world scenarios. Think task completion, SOPs, escalation and query-handling.
Deploy and Refine: Implement your AI agent, monitor its performance, and refine its capabilities based on feedback and outcomes. Ensure you lean on strong analytics and QA-ing LLM-responses.
2024: The Year AI Becomes Your Hardest Working Employee
As we peer into 2024, the prediction is not only the continuation but an acceleration of AI integration, across various departments and workflows.
The narrative will likely shift from AI as a novelty to AI as a necessity, with:
Wider Adoption Across Departments: AI will become a staple in departments beyond customer support, including HR, sales & marketing, and compliance.
Enhanced Interdepartmental Collaboration: AI agents will serve as bridges between departments, promoting seamless communication and unified workflows.
ROI as a Central Focus: More case studies akin to Tico will emerge, offering concrete evidence of the cost savings and efficiency gains achievable with GenAI.
Final Thoughts
The narrative for GenAI is clear: while adoption may currently be moderate, the success stories of early investment into productive GenAI (often found in Conversational AI), like Voiceflow's Tico, are paving the way for a future where AI is not just a support tool but a central player in business strategy.
If you haven't seen the viral Chevrolet ChatGPT-powered Chatbot, with users around the world trolling and force-hallucinating Chevrolet's chatbot – this is a CX & Marketers worst nightmare materialized.
Implementing GenAI isn't a flip of the switch – probably what happened for GM (Chevrolet), here. You can't just flip on your AI. Luckily before 2023's rise of LLMs & ChatGPT, we were working on Conversational AI automation for our Customer Experience, Support & Operations offering & ecosystem.
Tico, in its infancy, started from simple FAQs, evolving to help center retrieval and finally after many cycles, we're in a great position for automated support, our 'AGI'
With the rise of chatbots and text generation use cases, 2024 is set to be the year where the theoretical promise of GenAI becomes a staple of practical business operations, delivering undeniable ROI and reshaping the future of work.
Recommended reading: Tico, The AI customer support agent resolving 97% of tickets.
References
ML Insider. (2023). The state of Generative AI and Machine Learning at the end of 2023. Retrieved from https://cnvrg.io/ml-insider-results-2023/
Voiceflow, Pathways. (2023, December 11). Introducing Tico: The AI customer support agent resolving 97% of tickets. Retrieved from https://www.voiceflow.com/blog/introducing-tico-the-ai-customer-support-agent-resolving-97-of-tickets
AI humanizer | Stanford PhD | Cofounder & CTO @ MarvinLabs
8moTahsim Ahmed from my experience some of the issue stems from mentality gaps of people not willing to go the extra mile for AI integration. have you encoutnered that as well?