FYI: It’s not about the AI model, it’s how you use it ?

INSIDE THE BLACK BOX

Breaking down the latest in AI, customer service, and technology — so you don’t have to.

FRONT-END DEVELOPMENTS

?? WE’RE LOVING: Autonomous AI agents — but you heard it here first

?? WE’LL SEE: Call centers could become obsolete, and Gen Z is here for it

?? SAY LESS: When it comes to AI training data, you are what you eat

BACK-END BREAKDOWN

AI-powered digital avatars: The future of retail CX is a friendly face

Can digital avatars close the gap on truly personalized, AI-powered customer service? Some think so, claiming that face-to-AI-face interactions are what shoppers are missing.

?? SEMANTICS

• Digital avatars combine generative AI tools like voice cloning, LLMs, and facial recognition and reenactment technology to produce photo-realistic digital humans capable of holding real-time conversations with online end-users in multiple languages
• Like AI agents, AI-avatars can be trained on company data and embedded into their websites and mobile apps to enhance customer satisfaction and operational efficiency
• The digital human avatar sector is project to expand into a $500 billion market over the next 10 years

?? SENTIMENT ANALYSIS

Bad CX costs the US $75 billion annually. Are AI-powered digital avatars the solution? We’re not sure yet, but if real-time interactions with human-like AI-avatars are going to improve customer service, we’re all for it.?

Employees are bringing their own AI tools to work — and hiding it from their bosses

A new report reveals people across industries are using AI tools to work smarter. They’re saving time. They’re finding ways to be more productive. And they’re hiding it from their bosses. Are you as confused as we are? Let’s find out why.

?? SEMANTICS

• 53% of AI users surveyed worry that if their employers know they're using AI to be more productive or creative, it will signal that they're replaceable
• 66% of leaders said they wouldn't hire someone without AI skills, but employees say they're not being helped to get those skills — only 39% of employees said their organization provides AI training ?
• 79% of leaders believe their company needs to adopt AI to stay competitive, but 59% are worried they aren't effectively quantifying productivity gains from AI, and 60% worry their AI plans are insufficient

?? SENTIMENT ANALYSIS

This feels like a “duh" moment but we’ll say it anyway: Leaders need to start driving more adoption and investment in how employees can and should use AI in their everyday work lives.?

VENN ZERO

Anthropic recently published new research on AI models, giving people a glimpse into how models learn, understand AI safety concerns, and can become more controllable systems. Pair this with The anatomy of an AI agent and voila, you’re inside the black box.

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DEEP LEARNING

Customer service companies need to supercharge off-the-shelf models

In a recent report on the modern AI stack , Menlo Ventures published a very telling statistic: almost 95% of AI spend is now on inference (or running AI models) rather than training them, according to the firm’s survey of more than 450 enterprise executives.

The number represents a massive sea change. Not long ago, a much wider set of companies were training AI models, and it was thought most companies would one day create their own unique AI models from scratch. Whether to “build versus buy ” a model was a common contemplation among corporate IT teams exploring how to incorporate AI, and many set off building their own unique models for their own purposes.

“Teams seeking to build AI applications needed to start with the model — which often involved months of tedious data collection, feature engineering, and training runs, as well as a team of PhDs, before the system could be productionized as a customer-facing end product,” reads the Menlo Ventures report. “LLMs have flipped the script, shifting AI development to be more ‘product-forward’.”

In today’s AI landscape, companies like OpenAI, Anthropic, and Meta have done a lot of the heavy lifting, creating powerful large language models companies can tap as a starting point for their own products in customer service and beyond. But the widespread use of the same models has ignited a new approach to AI where it’s what a company does with a model once it's in hand that truly counts. Now that models themselves no longer serve as the main differentiator, companies are shifting their AI strategies to focus on supercharging leading models with their own data and processes.

Sage Lazzaro, Tech Journalist

READ ON

Ignoring the technology is not an option right now. Leaders who build for agility instead of stability and invest in [AI] skill-building internally will give their organizations a competitive advantage.

– Ryan Roslansky, CEO, LinkedIn

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