Three Reasons Why: Intelligent AI Interfaces are the New Business-Value Battleground 

By Leon Gauhman

From the arrival of GPT-4o to Project Astra – Google’s “AI-for-everything” agent – and new upgrades to the workplace “game-changer” that is Microsoft Copilot – this summer has opened up a new frontier in enterprise AI.

Big Tech is racing to unveil state-of-the-art intelligent systems that will transform the future of work, whether that’s a customised agent that can respond to a customer order without waiting for human instruction or a personal assistant that runs on real-time voice /text/code interactions.   

Key to these developments is the emergence of “multimodal” functionality: generative AI models that can combine data from a variety of inputs including text, images, video, voice and code. The result is a watershed moment not unlike when Mosaic launched the world’s first consumer-friendly web browser back in 1993.  

As with the dawn of the internet, we have yet to see exactly how these newfound capabilities — such as the ability to interpret human environments, create video from text, or lead live conversations — will take shape in years to come. But in a climate of intense AI rivalry in which even seasoned SaaS pioneers like Salesforce are struggling to keep pace, their impact on new-gen enterprise tooling will surely be profound.  

What practical use cases exist for this brave new world of multimodal AI and intelligent interfaces? How can businesses harness breakneck evolution to translate abstract potential into real-world value? Here are three core learnings:  

1. Personalised development and advanced decision-making 

Intelligent interfaces are rapidly creating an emerging class of AI assistants and digital employees. Natural communicators with inbuilt contextual awareness, these increasingly capable assistants may soon be woven into the architecture of all large-scale CX, HR, and project management systems.  

Take mentorship, an area of enterprise growth that can be complex and time-consuming to manage effectively. A predictive AI platform like Chronus can create personalised learning paths that consider each mentee’s unique needs and preferences — helping individuals at all levels access tailored support.  

In broader terms, the recent release of AI-powered assistant Amazon Q aims to help employees become 80% more productive at their jobs via sophisticated task delegation, data analysis and decision-making support. The company also recently presented two new capabilities for its AI agents in Amazon Bedrock, its wider enterprise platform. Memory retention allows agents to pick up info from previous user interactions. Meanwhile, code generation enables agents to generate code to help solve equations and optimise decisions based on changing data. 

2. Intelligent systems as standard 

Since this new wave of enterprise AI is about “taking the drudgery out of work”, it may quickly become more commonplace than we expect. After all, it’s been less than two years since ChatGPT’s revolutionary arrival, and already we’re discussing ways to make it less “slow” and “lazy”.  

In a similar vein, multimodal interfaces will deploy human-like capabilities in many areas of the digital workplace, becoming as intuitive to office life as a Zoom call or Slack huddle. Their main usage will be in the back office, as the beating heart of countless operations.   

However, AI’s creative potential is such that this superpower needn’t come at the cost of human jobs. US healthcare tech provider Empara recently launched a customisable AI virtual assistant called “Em”. Designed to respond to member questions about health benefits, policies, coverage and more – Em can significantly reduce call centre workload. The ultimate aim is to give healthcare professionals more time to focus on complex, intervention-led care issues.  

This new age of AI can invent whole new businesses, too. Mindtrip, for example, is one of several personalised AI-powered travel platforms that handle natural language chat responses alongside photos, maps, booking data and more. According to CEO Andy Moss, the concept behind the tool is “how do you use ChatGPT natural language but with a built-in killer consumer-facing interface that really ties in maps and data cards and flight schedules and takes it all the way through the booking.” 

3. Structural creativity: the big rethink 

If multimodality realigns how we interact with machines, this means we can redefine how human work is done. One of the biggest benefits of this latest chapter in human-centred design tech is how it enables an overhaul of everyday workflows and organisational structures.   

For example, security startup Command Zero uses large language models to support cyber investigators after a major security breach. Incident response professionals are taken on a type of “choose your own adventure” that aims to radically cut resolution times from hours to minutes – while identifying clues that may otherwise have been missed.   

Accounting tech company Xero’s JAX assistant can provide small businesses with personalised insights, troubleshoot customer issues, and offer forecasts to support human decisions. It anticipates and streamlines user interactions in a way that complements rather than replaces them.  

The rise of multimodal AI signals exciting times ahead for businesses of all kinds. By supercharging productivity and engagement, companies can add significant value to their market proposition.  

At the same time, this isn’t a vanity exercise: leaders must pay close attention to which tools have a tangible impact on day-to-day performance for AI to deliver on its promise of transformative change.

About the Author

Leon Gauhman is co-founder and chief strategy officer at digital product consultancy Elsewhen. The company recently made its debut in FT 1000 list of fastest growing companies. Elsewhen’s mission is to empower leaders to harness a cutting edge approach to design and technology to deliver positive impact for their organisations. Leon writes for publications including Sifted, Venturebeat and City AM. He loves using his experience in engineering and product to invest in promising early stage founders. Leon is also a member of the Bank of England’s Decision Maker Panel.
X: @leon