We’re here to put a stake in the ground that the next era of customer listening is HERE!
It’s happening right now.
There is a revolution occurring in how organizations will use conversational data in the next years and decades to immense value and impact.
Listening to conversations at scale unlocks the aggregation of topics, themes, and patterns to drive relevant and impactful insights to promote business outcomes and customer support. It embraces a more representative and inclusive approach to population data, which enables leaders and decision-makers to respond with a strategic plan based on an honest and informed view that spans the entire enterprise. By empowering the voice of the customer, healthcare leaders can take confident action with the full scope of an obstacle or opportunity in mind.
In the next year, the speed of AI adoption will continue, but there will be a growing need for more intentional questions, both philosophical and ethical, about how the innovation is integrating with healthcare. There will be some reckoning across the industry that must be addressed:
- What is the impact of AI on the industry?
- What are businesses and customers looking for with AI?
- Who is creating and reviewing the technology?
- What are people intending to create (short and long term) with AI?
- What will the industry need from AI for it to succeed?
Authenticx is taking steps to tackle these challenges by being intentional in building responsible AI. It matters not just what, but how our models are created, with trained data that deliver results to drive change in the healthcare ecosystem.
The Next Era of AI in Healthcare
Listening at scale means unearthing problems, but also highlighting outcomes and activity – unlocking the notion of monitoring efficiency and pursuing customer-centricity through the power of conversations.
First is the foundation, the next era of listening means we are leveraging AI as the means to the end we’re driving towards.
- Conversational AI trained for healthcare experiences is giving us scale to listen to a greater volume at a greater velocity.
- It means that algorithms have been trained specifically to address healthcare experiences.
- It means that regulatory realities are incorporated into predictions and listening compliantly.
Artificial intelligence has boomed exponentially since OpenAI’s ChatGPT release in late 2022. It is these types of advancements that have opened eyes to how AI can transform and improve healthcare. McKinsey & Company detailed how unstructured data — commonly, words exchanged in conversation via text or recording — provides an opportunity of immense impact to organizations and their customers. AI innovation is helping make that possible.
Using AI to listen at scale drives positive business and customer outcomes. Consider the following applications in healthcare:
- Audio to text transcription
- Image generation
- Tagging and labeling conversations
- Searching topics and themes
- Data summarization
- Topic identification
- Random sampling
- Autoscoring the quality of conversations
- Machine learning (ML)
- Deep learning
- Natural language processing (NLP)
At Voices23, hundreds of data points were captured during a discussion on the four core components influencing this new era of innovation: AI in Healthcare, Explore & Discover, Data-Backed Storytelling, and Take Action.
In considering AI for Healthcare, there was a clear desire for artificial intelligence to be leveraged to drive operational efficiency while keeping customer outcomes front and center.
Through conversational AI, we are creating the next era of customer experience metrics that gives your business the insight and confidence you need to make decisions.
When considering how to integrate AI in your healthcare ecosystem, consider the following two questions:
- What business problem are you solving?
- How have your AI models been trained?
See how technology like Authenticx is enabling this change.
AI at Authenticx
Artificial intelligence is transforming healthcare. Here at Authenticx, that means AI is being used to listen and synthesize conversations to help humans understand humans. This is a focused, nuanced approach that brings a level of reliability to data reporting.
The next era of listening means we are leveraging AI as a driving force of change to improve healthcare outcomes.
AI for Healthcare | Proprietary Authenticx AI Models
Conversational AI custom-trained for healthcare enables Authenticx to listen to a greater volume at a greater velocity. This means algorithms are actively being developed to compliantly provide insights on healthcare experiences.
Humans are also a key component of how Authenticx approaches AI. Our architects and analysts leverage their own professional healthcare experience, intentionally training algorithms with healthcare-specificity. This work is supported by data labeling linguists, who come from backgrounds in healthcare, education, and social work, to listen and label calls.
This approach is a robust, comprehensive AI-powered offering with unrivaled capabilities to listen at scale.
Conversation Summary is a Generative AI Large Language model (like ChatGPT) that creates new content (the summary) from existing content (the original conversation). Authenticx Conversation Summary is leveraged for every conversation uploaded into the Authenticx software and feeds into the product features seen by CRM (customer relationship management) users. This model is proprietary and uses an in-house product engineering team that enhances the model for reliable and timely results, and it is available via an API (application programming interface) agreement.
Eddy Effect™ is the only commercially available customer friction model that directly ties to ROI measuring friction. We are improving how our AI model correlates identified friction points (‘Eddies’) and goes deeper into identifying root causes. This model is a leading differentiator that is years ahead of industry standards, already unearthing healthcare-specific points of friction.
Adverse Events is a model that surfaces adverse events and other risk factors. This isn’t a model that just flags the presence of a risk factor, but provides context on how agent responds to the presence of these AEs that remains HIPAA compliant. This provides an added layer of security to drive compliant behaviors.
Sentiment is a model that captures customer sentiment. Human analysts will continue to check, refine, and hone this model over time. This model provides an early indicator behind what is driving calls and how the customer may be feeling. This is valuable, particularly in healthcare, as sentiment can highlight both positive and negative operational impact.
Simply put, listening matters. Without intentional listening, you risk missing critical customer voices that signal early warning signs of trouble – signals that we need to protect and strengthen our businesses, customers, and employees. We are living in a time of profound change and opportunity. With the help of AI, healthcare organizations are better equipped than ever to not only listen, but to listen at scale. The next era of customer listening is here.
Authenticx was founded to analyze and activate customer interaction data at scale. Why? We wanted to reveal transformational opportunities in healthcare. We are on a mission to help humans understand humans. With a combined 100+ years of leadership experience in pharma, payer, and healthcare organizations, we know first-hand the challenges and opportunities that our clients face because we’ve been in your shoes. In 2023, Authenticx was ranked No. 349 on the Inc. 5000 recognized as one of America and Indiana’s fastest-growing private companies.
Want to learn more? Contact us!