Empowering Developers with Conversational AI – Business 2 Community

AI and automation are rapidly becoming an integral part of modern software development and business applications. However, far too often the focus is placed on offloading developers and other teams rather than addressing or improving the actual developer and user experience. Instead, businesses should rethink their stance on AI from a developer replacement, to a developer enhancement.

Consider the requirements for modern software development and the time that it takes. Engineers can spend months, if not years reverse-engineering years of code and communication protocols in order to effectively build the automated workflows and experiences that drive user productivity and adoption. Implementing highly sophisticated AI/ML algorithms can substantially reduce development time while also allowing developers to leverage cutting-edge features that are powered by AI. The combination of all of this means shorter development cycles, quicker time to market, and more intuitive and intelligent workflows and experiences.

The time is now for businesses to invest in AI-driven developer experiences, and the numbers back it up. In a report published by PMI, AI innovative companies achieve higher rates of on-time delivery and greater ROI. It is clear that arming developers with conversational AI tools and features provides immense value, but the how might not be as obvious.

Whether it is through the implementation of a single, or multiple APIs, or internal builds, here are three ways developers can quickly and easily leverage AI in order to more effectively build automation and innovation that creates more efficient teams and experiences.

Intelligent Extraction
There is a wealth of critical data sitting in our email inboxes just waiting to be put to work. More specifically, within attachments such as PDFs, images, email signatures, and more. Documents and attachments such as invoices, travel information, shipping logistics, meeting details, and more all contain rich data that once extracted, can be leveraged within multiple applications, workflows, and teams. Rather than going through the traditional process of downloading these attachments and manually updating systems and applications, developers can use AI-powered data extraction tools to eliminate time-consuming processes and reduce human error.

With just a few lines of code, tools such as Optical Character Recognition (OCR) developers can build intelligent data extraction workflows and applications. Leveraging AI, developers can identify and harness critical business and communication data that lives within these documents and automatically extract the data and populate it within connected applications. For example, developers can build automated workflows that extract rich PDF data, such as invoices or business contracts, and automatically populate and update CRM records, ensuring that system and customer records stay up to date at all times. We’ve seen direct use cases such as extracting PDFs such as invoices or receipts to more efficiently track payments, billing cycles and status updates, and more.

Contextual Filters
Key data and important business context can easily get lost in ongoing conversations that involve multiple people. We’ve all been a part of long email exchanges comprised of numerous people, attachments, responses, away messages, and much more.

With conversational AI and tools such as Natural Language Processing (NLP), developers can build tools that automatically clean up messages and conversations by sifting through correspondences and removing unnecessary responses and information. This process not only makes it easier to identify and extract critical data, but it can also over time significantly increase user productivity by saving countless hours of searching through inboxes and messages to find what is needed.

Contextual filters can be great for customer-facing teams, as they can easily parse through conversations to quickly address customer requests and needs, identify action items, and prioritize communications and conversations.

Automated Workflows
On the surface, things like data entry, application toggling, or context switching seems like outdated, but necessary components to everyday business, but the reality is, these processes are impacting businesses both in terms of lost productivity and financial growth. For example, in a global study conducted by Unit4, office workers spend around 69 days per year on administrative tasks, representing around $5 trillion per year in lost productivity.

Data insights generated from Conversational AI can serve as a trigger to automate a manual task. Now, critical data can automatically be entered into system records, applications can be synchronized to reduce channel switching, distractions, and lost productivity. For example, automatically update or reschedule meetings based on out-of-office notices or conflicts. This type of automation saves time and money and allows developers and their entire organization to spend less time on mundane tasks and more time truly focused on delivering meaningful business contributions and results.

Software is truly eating the world and is the lifeblood of digital transformation and modern business. As a result, developers have become not only essential components for building and scaling products and services but are now crucial to business growth and ROI.

Applying AI and automation helps developers, product, and engineering teams achieve operational efficiencies throughout the development lifecycle as well as create and build intelligent workflows and experiences for individuals and teams throughout an organization, including sales, marketing, HR and recruiting, and more.

Unifying data across multiple platforms, channels, and interactions, gives developers the baseline needed to put that data to work through conversational AI features that can create more efficient and intelligent workflows, automate tedious tasks, and deliver better user experiences.

The time is now to empower developers with disruptive technologies such as conversational AI, machine learning, and more, and give them the modern tools needed to drive productivity, change, and impact across an entire organization.


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