How Appian's low-code platform powers consultants (and their clients)

US-headquartered Appian is one of the world’s leading providers of platforms for low-code software development. During his recent visit to Australia, we sat down with Co-Founder and Chief Partner Officer, Marc Wilson, to discuss how Appian is helping consultants make more of an impact at their clients.

How can business consultants effectively leverage AI, low-code, and process automation to drive improvements in business operations?

Artificial intelligence (AI), low-code and process automation need to be considered as a holistic way to tackle business problems. These technologies should be viewed as tools that complement one another – all of which are essential to work together for modern applications.

From a consulting perspective, end-to-end process automation begins with discovery, where process mining and workflow automation play a crucial role. AI is increasingly becoming a vital part of that. It manifests itself in Appian’s platform in a few different ways – all of which are important for the consulting world to understand.

First and foremost, we're leveraging AI to help make processes move even faster. For example, we’ve trained generative AI models to effectively code in Appian. By describing the form or application that you want to construct, it will build large chunks of that application. Again, this feature saves consultancy time in getting an application ready for a customer.

The second major aspect of AI is the integration of algorithms into decision making and actions within a process and application itself. For example, intelligent document processing permits the evaluation and classification of various documents, streamlining processes like loan applications or public sector files. These algorithms also contribute to decision-making within processes, determining their flow and assigning tasks based on models.

Can you provide an overview of the Appian partner ecosystem and how implementation partners or consultants can add value for clients?

By its nature, Appian is a platform that lends itself to effective consulting. We provide a platform where organisations can effortlessly design and deploy applications by integrating forms, reports, process models, and more with a simple point-and-click approach.

The continued development of Appian's partner ecosystem certainly has followed in line with that and we're very proud of what we've been able to develop, not only globally, but here in Australia. We’re seeing significant strides with our consulting advisory partners, as well as continued development with our system integrators, both large and small. We've seen a virtual explosion in the number of practitioners for Appian in the market, which also extends to two other kinds of partners.

The first is technology partnerships, where they complement what we do, whether they're large organisations like AWS or large application providers like Guidewire. Both relationships are global in nature, but we're excited to see what we've been able to bring the local market with those relationships.

The second is reseller and distribution partners who are looking to take Appian into different markets. We’re really catering to those kinds of partners today because we're looking to ensure that we can be as broad as possible – leveraging the partner ecosystem is an essential part of that.

What are the essential considerations for business consultants when evaluating AI and low-code solutions for organisations? And can you talk about issues around public versus private AI and how Appian is helping consultants address these issues?

I think it's very difficult for consultants today to solely look at a single feature set. The reality is a great AI algorithm alone isn’t enough to bring value to a business or organisation. Instead, we need to consider how the AI solution can be effectively integrated into an organisation's existing processes and operations. For AI to be truly valuable, it needs to be operationalised within the organisation's workflow and environment.

The discussion about public AI and private AI is something we view as an essential debate and discussion over the next five to 10 years. Appian’s legacy is working within very secure environments. We tend to work with the kinds of applications that touch sensitive information from a competitive perspective, a personal perspective, or healthcare information, and financial information.

The work that we've done with governments both in Australia and around the world speaks to, again, citizen information or national security information. Security is vital to us and our whole architecture and infrastructure has been built around the notion of security first.

However, AI brings a new element to this. A lot of the popular discussion around AI of late has largely been around public AI algorithms. For example, something like ChatGPT has algorithms that are being fed by hundreds of thousands of users adding new pieces of data, requests, or information. That's how these algorithms are learning, which is great in our personal lives but that's not the kind of information or the kind of approach that a bank or public sector agency would want to take.

In the context of business, organisations like this would never want to share their constituent information or customer information with an algorithm that is outside of their control or with the potential to expose information to a competitor or the public. Consequently, what we’ve already started to see is the development of private AI algorithms, where data is 100% under the control of the organisation that's trying to create, teach, expand, and make that algorithm more efficient.

Appian recognises the need for private AI, and while we may occasionally link with public AI algorithms, our focus is on integrating private AI capabilities into our platform. We want to ensure our customers have faith in the algorithms and maintain control over their data, providing secure and efficient solutions tailored to their specific needs.

Can you provide some examples of how a consultancy firm could successfully utilise AI, low-code, and process automation to solve complex business challenges and optimise operations within an organisation?

We've already started to see some examples in the first iterations of AI used for intelligent document processing algorithms. This is most often in areas where there are a lot of documents that follow processes, such as applications that require documentation for the creation of an account, an insurance policy, or processes and approaches that require a lot of documentation in the middle.

Training these algorithms for applications that enhance efficiency can drastically reduce review times from weeks to minutes or hours. They improve human decision-making and enable risk assessments on incoming documents.

These applications have largely come from the organisations’ increased focus on customer satisfaction. While people once accepted the fact that something might take weeks, they simply won’t anymore. They expect systems to operate far more efficiently. When you're dealing with organisations that might be looking at tens of thousands of documents each day, whether that’s paper or virtual, you’ve got to find a way of processing those much more quickly.

I think all consultants should be looking at the processes they create and thinking towards the future – how could this be done quicker? Process mining helps identify bottlenecks, improve efficiency through automation, and opens discussions on automating steps further with AI and algorithms for faster outcomes.

How does Appian's platform enable business consultants to bridge the gap between business requirements and technical implementation, particularly in the context of AI, low-code, and process automation?

Appian enables things to move much faster. The days of “let's do an assessment and write up a report on what we might want to do” which might take three months, are gone. Today we're seeing that compressed into hours. Again, this is where process mining can help to bridge anecdotal reviews of the as-is state with quantitative reviews of the as-is state. That combination allows things to move much quicker and identify places where improvements can be made.

Speed in application development can also be aided by the platform being used, allowing things to be bypassed which might traditionally take a little bit longer. For instance, you might want an algorithm to improve a particular area of a process, but using traditional development, that algorithm might take much longer. Maybe the data doesn't exist, or maybe the personnel don't exist to get that done.

What Appian is trying to do is take away all the roadblocks – none of the hurdles around waiting for data or waiting for something else to apply anymore. We’re busy teaching the market you don’t have to wait, and you can get started today.

Looking ahead, what trends or advancements do you foresee in the field of AI, low-code, and process automation that business consultants should be aware of?

I think that the world has reached a point where people are understanding that even an algorithm is a feature, it's not an end state, it's not a product in itself.

Organisations and consultants really need to think strongly about their data strategies. They shouldn't be going with approaches that require data to be in a certain siloed location, because the evolution of what we're looking at is constant change. I think we want to break away from a world where you build an application, it has a five-year lifespan, and then you have to rebuild it all over again. You must enter a phase of continuous improvement and adaptation, with the ability to take on new approaches, new algorithms, or new technologies as you move along.