The time for talking is over. 2024 will be the year when enterprises worldwide are judged by the outcomes achieved when generative AI is expertly applied to data processing. Appian’s Randy Guard talks to NZBusiness about the advantages of fully utilising their “trusted and game-changing” automation technology.
Think process automation and process orchestration. Indeed, consider any enterprise-level workflow – such as financial compliance, insurance claims or manufacturing processes – processes that are complex and leverage large amounts of data, all with the aim of getting things done.
Artificial intelligence has now become their great enabler, and a remarkable driver of greater efficiency.
“AI is a game-changer, but the only way to fuel that engine is to bring it data, and lots of it,” says Appian’s CMO and B2B tech marketing leader Randy Guard.
Data-process AI is what Appian is all about, he says. “But Appian is not a database, so companies don’t have to put all their data in one place.”
“Our approach is the exact opposite. We call it ‘data fabric’. We apply it across your enterprise and then simply connect your data.”
No new machines, disk-drives, or databases necessary, he says. “We allow you to access that data, we respect all of its security and authentication requirements, and we let you write it back.” It’s a trusted, bi-directional approach to data processing.
Appian is extremely focused on private AI. “Because we’re very conscious that our data fabric allows you, the customer, to be super-confident that all your data is your data,” says Guard.
Appian drives the whole process – providing clients with a low-code or no-code platform to build a process, to set up access and deliver the outcomes required.
As examples, insurance companies use data-process AI for claims processing; financial services companies use it for customer service or regulatory compliance.
Guard cites one large financial services company that uses the technology for risk governance compliance work.
The whole aspect of enterprise process management is critically important as well, he adds, and it’s all complementary to AI.
“AI could be deployed for intelligent document processing. It could be for semantic search,” explains Guard. “Today, we marry generative AI with data process; we have clients using generative AI in customer service.
“Think of a chat or an automated customer service engagement. For example, you might have a warranty claim from a customer. We can use generative AI to allow a customer to use it within a process app.”
The challenges of implementation
Fundamentally AI works for multiple-use cases, and generative AI is the biggest, most prolific AI technology in use right now.
Guard says Appian are experts at putting AI into operation. “We are focused on operationalising AI so you can scale it out. That’s where the value lies.”
The first challenge when implementing AI at an organisational level lies around privacy, he says. “Particularly if you’re a B2B company. You’ve got to protect your data.”
The second challenge is operationalising the technology – putting it into more of a defined and structured approach and letting the AI do what it must do.
“The third challenge is getting over the fear of ‘AI is going to take over our jobs’, as well as the fear of not knowing what you’re going to get. That’s where we believe in this concept of mixed autonomy.”
AI can be great for content generation, but at the end of the day, people need to be the final editor, he says. “Many decisions can be automated and performed in milliseconds. AI can make some great recommendations, and decisions, but people in your company must ultimately create that decision framework.
“We’re big fans of mixed autonomy. We believe AI is a big part of the future, but it’s not on autopilot. We believe leveraging human talent with AI’s process intelligence is the key.”
Your co-pilot
Companies need a trusted technology partner, so they can be confident that their enterprise data is not being compromised.
Appian has implemented AI into its tooling, says Guard, which does indeed work as a kind of co-pilot for their customers when building software, or perhaps that chat engagement with a customer.
The Appian AI Process Platform works because we’re not all experts in algorithms or generative AI, says Guard. “We use this approach to help provide guidance for non-tech users.
“We have AI skills that are broadly developed for developers, users, and executives. We’ve enabled that and empowered that in the Appian platform.”
Guard says their retention rate with clients is industry leading, and he attributes that to not just the huge investment they have in Appian’s AI process automation technology, but the value that those clients get from it.
The equalizer
Don’t approach AI as if it’s going to know and solve your business better than you can, warns Guard. It’s always going to be a supporting tool and technology.
However, AI can be an equalizer between those larger, well-funded organisations that have a tremendous amount of highly skilled data science talent, and other smaller, less resourced companies.
As AI progresses it will start to neutralize the playing field, says Guard. “A mid-size or large enterprise will have access to that same capability. “So, it does create a little more democratisation of AI and analytics, and companies will be able to evolve much quicker.”
Addressing privacy concerns
It’s understandable that people will have concerns around privacy when it comes to incorporating public AI models into their data processing operations.
“First and foremost, you want to be careful that your data doesn’t become somebody else’s product,” says Guard.
“In regard to some of the bigger providers of generative AI, if you’re not careful, any questions or data that you’re submitting can be part of their product and their evolution. So be super careful around what you offer up for them to incorporate into their model,” he says.
Appian has market-approved techniques they use to ensure that your private data stays absolutely private.
With data being such a vital asset, that’s very important, he says.
Other Articles
