2023 was the year of artificial intelligence. But 2024 will be the year of practical AI applications. While many organizations have employed AI for decades, others were faced with mandates from leadership to use AI without knowing its full, pragmatic applications.
Let’s change that.
AI isn’t an end; it’s a means. When you apply AI capabilities to the right use cases, you transform the heart of your organization. Virtual assistants can help human experts perform better. Large language models combined with generative AI can craft emails and meeting summaries. AI-based analytics can analyze vast amounts of data that humans alone could not.
This post will discuss several artificial intelligence capabilities that any enterprise can adopt to turn their organization into an efficient, effective powerhouse.
[ What’s in store for AI this year? See predictions from eight AI experts in the 2024 AI Outlook: Expert Advice on Navigating the AI Economy. ]
AI capabilities: practical steps for improving your organizations
Prior to 2022, a lot of the AI news centered on use cases like self-driving cars. Of course, use cases like these didn’t exactly apply to enterprise software. In 2023 ChatGPT showed the abilities of AI to mimic human language, but still, this only scratched the surface of AI applications for the modern enterprise.
If you’ve ever asked yourself, “What is AI capable of?” then consider the following examples:
1. AI document processing.
How many emails do you get per day? How many documents do you have to sift through? Depending on your department and role, you may be flooded with hundreds. Insurance claims processors, billing specialists, or customer service reps can feel close to collapsing under the weight of the avalanche of documents they have to process.
AI capabilities can enable teams to rapidly process content. With an AI process platform, you can create your own AI algorithms that classify incoming documents and extract data to be easily used in other applications. This can free your workers to focus on reviewing the AI system output, escalating challenging exceptions, and working on higher-value projects.
[ Did you know you can create your own AI algorithms without sacrificing data privacy? Learn more with Implementing Private AI: A Practical Guide. ]
2. Generative AI correspondence.
Generative AI enables anyone to create content or media quickly. This includes humans using prompts for Dall-E, Midjourney, or ChatGPT to produce new content. But in a business setting, generative AI can also be used to build applications that generate emails on the fly, saving significant time for workers.
Think about the applications of these AI capabilities. Airlines can quickly create and send rescheduling responses to customer inquiries about flight delays. Insurance companies can generate answers to customer service inquiries or build policy documents fast. Billing departments can craft collection emails and inquiries at the click of a button.
It’s important to keep in mind the limitations of these AI capabilities, however. Generative AI can hallucinate—or more simply put, create unintended outputs or errors—so it’s critically important to keep humans in the loop for oversight.
3. Analytics.
Artificial intelligence works similarly to human intelligence. AI learns from examples and experience, takes in a vast amount of data, then makes predictions based on its learning set. This process makes it a perfect fit for any analytical project.
Most analytics are descriptive, focusing on the current state of an environment or situation. For example, an insurance company might view reports on the number of claims submitted by customers. This is purely descriptive, and businesses must project outward from there. However, these companies can use AI to bolster their descriptive analytics and insert predictive analytics that suggest possible outcomes. Taking the same example, AI could quickly analyze multiple data sources and spot patterns around why claims have been increasing that humans can’t easily see (such as weather patterns or an increase in climate change–related natural disasters leading to more home insurance claims). Analyzing this amount of data can quickly become overwhelming for a human, but with the right compute power, AI can enhance human intelligence.
And AI also shines with predictive analytics. This could come in the form of suggestions on how to offset the claims increases or boost revenues with new products. Predictive analytics technologies with AI also allow you to model scenarios such as price increases to see what the effects could be on your bottom line (and how many customers might seek out competitors instead).
4. Software development.
Software engineering has been on a consistent trajectory towards faster, more efficient coding. From the early days of machine language to object-oriented languages to development frameworks to low-code, software engineering has consistently moved towards greater speed and agility. Now, AI provides even faster, more powerful development for those building applications (particularly enterprise software).
One example? Building interfaces. A strong AI process platform can help you take a simple PDF form, then automatically generate a full application interface from it. Normally, this process would involve design work to decide which fields to include, front-end coding and styling, back-end coding to transfer data to the appropriate database, and database programming. With AI capabilities (combined with strong low-code capabilities and data fabric), you can generate these forms in seconds rather than days.
5. Knowledge management.
Want to speed up customer service and improve customer experience? Use AI to give customer service reps the right information at the right time.
Think about an insurance claim handler dealing with an auto accident payout. They receive a report for a damage claim that occurs outside of the person’s home state. The insurance handler must find information about interstate policies for the organization, legal issues, etc. They may need to spend hours sifting through multiple databases, handbooks, and policy documents. It’s time consuming.
AI can cut the time this takes. By training an AI model on your documents, knowledge bases, and even legal documents, you can set up a system that provides real intelligence to insurance agents in nearly real time. And if this information is traceable to the original documents, then AI can allow the agent to check information to ensure greater accuracy.
The AI capabilities that will transform your organization.
As we come to grips with living in the AI economy, businesses can deploy AI capabilities that help them come out on top. From streamlining document processing to enhancing customer experience, AI can reshape the way businesses operate. The implications of these AI advancements are profound. From faster task completion to better decision-making, the right AI capabilities can have a transformative impact on any organization. The question is no longer about the potential of AI—it’s about how to strategically and thoughtfully deploy it to harness that potential.
So, what will you do with AI?
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If you want to operationalize AI in your organization, it helps to put it in the context of a wider AI process platform. Appian provides the capabilities to help you do this, from process mining to a complete set of automation tools to low-code design. Don’t take our word for it—you can get an unbiased third-party opinion by downloading the Gartner® Critical Capabilities™ Report for low-code.
