Recent advancements in generative AI—like GPT-4—are changing what’s possible for companies and people to achieve with technology.
But the truth is, to get the most out of generative AI, you need to leverage it operationally.
That is, you should make it a core part of your internal processes.
This might seem obvious, but consider the use-cases for AI you see most on social media. Generally, the hype is grounded in AI's capacity to generate net new content. This is great, but how can you use the power of something like GPT-4 in more than one-off cases? To do more than write blogs? Can AI change the way we work across the board—for the better?
To get the absolute most out of AI, you need to leverage it in a way that’s structured, accessible, and repeatable at scale. That comes down to building it into your everyday essential processes. GPT-4's problem solving capacity is perhaps only matched by AI's ability to help us make our processes easier, faster, better.
This handbook will walk you through ways to do just that—along with examples of what exactly this looks like.
Every day, organizations fail to either identify or capitalize on potentially valuable business insights. That's because they hit departmental intake channels—from procurement to legal, invoicing to customer success—in the form of unstructured text.
Formerly, that data was unusable, or at least time-consuming to identify. Internal service teams would need to monitor these channels manually.
Now, you can capture (and take action on) those valuable, unstructured insights by employing AI models to monitor intake channels for you and to then summarize and classify what-all unstructured text comes through—whether it comes in via external or internal requests.
By leveraging technologies such as OCR, NLP, and, now, generative AI like OpenAI GPT models, internal teams can more rapidly understand and categorize the business context, sentiment, and intent of any kind of operational request.
What's more? The data derived from this automatic intake analysis can then be funneled to and organized within a single-source-of-truth backend portal, where all parties can assess the data—both for immediate high-level understandings, as well as to track the status of requests.
If this all sounds like a lot, don't worry—AI-powered business process automation platforms like Tonkean package all these capabilities for you in a no-code interface, allowing internal teams themselves to set up these kinds of AI-powered intake solutions on their own. Partnering with one such platform—which functions, above all, to put structure around the raw firepower of AI—is a good place to start in your AI implementation efforts.
AI can help you go beyond saving yourself time on the backend of key processes.
For example, with AI-powered automation tools, you can begin resolving your employees' requests and solving their problems proactively—in some cases enabling employees to go from request to resolution in seconds.
Such tools include the new Tonkean AI Front Door, which allows internal teams to set up GPT-powered personal entry points for all internal processes.
With something like this in place, the experience of asking questions of or submitting requests to teams like Legal or Procurement looks drastically different. Example: now, when employees need Legal to generate an NDA for them, instead of sending an email, all they need to do is access the Front Door and type "I need an NDA for Account XYZ." The Front Door checks for existing documents, generating a new one if needed, and even initiating e-signature workflows with a single click.
Such a tool also allows you to fully automate previously laborious processes such as tail-spend processing, or, “three bids and a buy." It does so by automatically identifying appropriate purchase categories, analyzing vendors’ websites, extracting their benefits and capabilities, suggesting alternatives, and generating RFI/RFPs—all within seconds of employee entering their initial information.
Now imagine that you’ve changed the status of a new deal inside Salesforce—but did not take the sort of additional action you’ve taken in similar instances in the past.
Before, you'd have to remember and go back into Salesforce to complete the action.
Now, with AI, you can create processes that will reach back out to employees proactively. Tonkean, for example, will notice you've changed a deal's stage and, based on past behavior, proactively creates an MSA, asking if you need any revisions or changes, saving you time and effort.
Like all previously seismic advances in technology, AI can seem like magic—but really, it's just a tool.
Key to getting the most out of it is understanding that AI is fundamentally just a tool (or a set of tools). You have to learn what it’s for, how it works, and how to use it safely and effectively.
That starts, in our mind, with people. Successful operations generally are about enabling people to do better, more meaningful work. You have to optimize the experience around your processes for your users. You have to make life easier for them while accentuating their best attributes. Great implementations of technology are about augmenting what humans can do, not replacing them.
That’s what AI can do. Or rather, that's how we should strive to employ it.