#lowcodeautomation

Relationships are hard work. And without good communication, they become strained - regardless of the circumstances. Broker and underwriter relationships are no different. Whether you’re a broker trying to build and maintain rapport with customers or an underwriter trying to assess submissions and determine acceptable risk, a shared understanding of each side's priorities, goals, and pain points is key for healthier relationships and faster processes. That’s where insurance modernization can help.

NatWest tasked Appian with a handful of key objectives related to one of their policies, the Change Risk Review process: to maximise efficiency, provide simple and intuitive ways to meet governance needs, and automate change governance to reduce duplication.

Matt Calkins, the cofounder and CEO of Appian, a leading provider of low-code automation solutions, has thrown down the gauntlet to the AI industry. This week, Calkins unveiled a new set of guidelines designed to promote responsible AI development and build trust between AI providers and their customers

Medical affairs has grown to become a core pillar of the pharmaceutical industry, linking the work of research and development and commercial operations. However, for leaders in the industry, navigating the process and data complexities and communication silos involved can prove challenging. The integration of artificial intelligence (AI) to respond to these challenges and boost efficiencies throughout medical affairs can greatly impact the industry moving forward. Here are three ways AI can support innovation.

Surveys by Sollers Consulting and Ipsos show that customers expect their insurers to process claims quickly when they make a claim. Insurance companies are struggling to respond to customer demands. Sollers and Appian expect the industry to intensify claims automation efforts. Fast claims settlement is the most important thing for insurance customers when it comes to claims handling.

Matt Calkins, co-founder and CEO of Appian, said that though giants like Microsoft, Amazon and Google are spending billions on the tech, ensuring success in AI is “not just about money.” Referring to deals and partnerships between tech giants and smaller AI firms, Calkins said, “If coalitions won the AI race, Google would have won by now.” “The fact that you’ve got enough money to buy, or buy a piece of, Anthropic or Mistral or any of that, that’s impressive — but AI may not be a ‘winner take all’ market,” he added.

Process mining is taking on an increasingly important role within Appian’s automation and orchestration platform. It should provide both more insights into organizations’ processes, but also into the underlying Data Fabric. Of course, there is also the necessary space and focus on AI in version 24.2, with the Appian AI Copilot as the main exponent, in addition to eleven new AI Skills.

"The role of humans is actually going to become ‘more human’ as we continue to enter the AI economy." (Appian CEO Matt Calkins). The rise of low-code application development technologies designed to perform software architecture and workflow process automation and acceleration has been hugely prevalent in the way modern (increasingly cloud-native) IT systems have been built and operated. Software platforms at this level now have an essential responsibility to work with data in a unified, secure, discoverable and optimized way - and this is a reality significantly amplified by the arrival of generative Artificial Intelligence (gen-AI) and its impact on business operations and human welfare.

AI went mainstream in 2023 dominating news headlines, LinkedIn feeds, and business conversations. However, despite witnessing significant progress over the past year, we are only at the cusp of AI’s potential. For the banking and financial services industry, AI isn’t just a new tech trend. It’s a powerful tool that will have a wide range of impacts, from risk management to operational efficiency and customer experience.

While generative AI offers great potential to accelerate productivity and innovation, it poses new challenges to business leaders. For instance, how do organizations prepare their workforce for a future where humans and AI work together to make critical decisions and complete complex tasks? How can they adopt generative AI safely across the business? How do they make sure that no one is left behind?