By Alf Saggese, Chief Revenue Officer at TrustPortal
GenAI holds huge potential for enhancing services by raising productivity and cutting costs.
A study by UKG shows that 78% of C-suite have embraced AI within their business frameworks. EY research reveals that by the end of 2024, 88% of companies will invest to fortify their AI capabilities.
From speaking with automation and business leaders, they are urgently seeking innovative ways of employing GenAI to augment services across their organisations’ front-office and multi-channel operations.
But in the race to harness GenAI, many organisations find themselves at a crossroads. Cisco's study reveals only 14% of companies feel truly equipped to employ AI comprehensively.
The reality is that most enterprises have been unable to move beyond hypothetical use cases and POCs. HFS research also asserts that while 37% of business executives aim to scale Gen AI within 2 years, 42% cite a lack of use cases.
An AI reality check
For most organisations, trying to develop enterprise-level GenAI applications is like trying to solve a puzzle in the dark. Why?
It’s not from a lack of ambition. It’s because enterprises aren't clean-slate startups. Many are discovering that GenAI's potential is often constrained by integrating it with legacy systems, applications and processes.
And let's not forget the elephant in the room: GenAI isn't infallible.
While GenAI excels at understanding intent and context, it's not immune to misunderstandings or limited data access, which could lead to costly errors, particularly in sensitive operations like financial transactions.
These problems will be amplified as GenAI tools begin to interact directly with applications and execute more themselves.
An automation-AI synergy
Forward-thinking transformation leaders are increasingly recognising that the true potential of GenAI can be harnessed when combined with automation.
This synergy allows for safe testing and swift deployment of GenAI tools across the enterprise by incorporating them into newly designed automated process flows.
The beauty of this approach lies in its non-disruptive nature – existing systems remain intact, eliminating the need for major process overhauls or mass data migrations.
HFS Research’s latest Pulse data of 600 Global 2000 enterprises says 2024 tech budgets are rebounding and the core drivers are AI and automation.
However, before hailing automation as the definitive 'on-ramp' for GenAI integration into business operations, three key considerations must be addressed:
1. Automation tools must work harmoniously with both legacy and cutting-edge technologies, especially in dynamic, time-critical environments like contact centres and across multiple channels.
2. GenAI's output must be carefully monitored, with processes in place for real-time "human-in-the-loop" intervention to maximise productivity and mitigate risks.
3. All these elements need to be orchestrated and actioned instantaneously, and at a significant scale.
Enter Intelligent HyperAutomation
Intelligent HyperAutomation represents a positive mind shift in how organisations approach GenAI integration.
It involves the strategic design and delivery of processes that enable multi-automation vendor software robots to collaborate seamlessly with employees, GenAI, legacy systems, and digital technologies.
They’re all intelligently orchestrated as a ‘hyperAutomated workforce’ communicating and co-working via real-time dialogues to perfectly perform every step of any process.
They do this across complex and ever-changing, old & new IT environments – and via any channel, including chatbot, email, SMS, voice recognition and more.
Digital workers (from any vendor), perform real-time access to any system.
Digital workers dynamically generate contextual UI’s for every stage of a process, across any channel.
AI, including GenAI, determines need, context and data from channels, systems & images.
People, including employees, provide immediate input, review, approval where needed.
What does this look like in action?
Picture this: an insurance company drowning in ambiguous claim emails. Normally, this would be a recipe for missed deadlines, angry customers, and stressed-out employees.
But with Intelligent HyperAutomation, GenAI figures out what the customer wants, the system pulls relevant info from multiple databases, and an employee gives it a final once-over before sending a response. This can dramatically improve response times, reduce costs, and meet those SLAs.
Intelligent HyperAutomation is helping smart leaders within front office environments of leading brands including Telefonica and EDF, action new ways to integrate GenAI into their existing data strategies.
They are testing where GenAI’s impact and ROI can be measured, building case studies and showing value that can be scaled across their multi-channel operations.
A UK energy company has already used AI to address email processing, including training NLP on 10,000's of emails. However, NLP only improved routing and reporting - not delivery of responses. To deal with this complexity, they are using HyperAutomated GenAI to improve the agent experiences, deliver faster response times, cost savings and better adherence to SLA’s.
There are also opportunities for companies to assist business customers who use more complex emails. They can make email processing easier to use for agents, by providing a simple view of what's outstanding, SLA reporting and more.
Bottom line
While Intelligent HyperAutomation isn't a panacea, it offers a pragmatic approach for companies seeking to navigate GenAI landscape, without wholesale reinvention. It's about optimising existing resources – human capital, legacy systems, and cutting-edge AI – to drive tangible business outcomes.
So, while everyone else is chasing the next big GenAI breakthrough, maybe it's time to get smart about using what's already there. And the best part? It might actually save money and time, instead of just being another expensive tech experiment.
As the GenAI gold rush continues, the true winners may well be those who embrace Intelligent HyperAutomation. In fact, this approach could be the key to delivering faster, more productive, multi-channel services.
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