Move Forward With Control, Confidence, Trust, and ROI

Given the immense publicity for Generative AI recently, most companies are now evaluating their options to tap the technology, with keen interest but also caution. On the one hand, there are a number of options to consider, based on large language models built on internet content. The publicity has caused many to evaluate how they could possibly tap into this for business use.

At the same time most organizations are well aware of the tales of irrelevant, generic, false, or legally risky uses. This tends to slow down decisions, while companies rightly conduct diligence, and determine if there are valuable ways that they can control the technology and use it with confidence.  

A Thoughtful Approach IS Warranted.

There are quite a few elements to consider, and there may be many voices in each company with different views.

• What are the critical business purposes and opportunities?
• Are we looking for efficiencies, new capabilities, growth, cost-cutting, a competitive advantage?
• How much should we take on, and in what timeframes? What are our priorities?
• What are the ‘low-hanging-fruit options?
• What are the impacts on specific people, groups, staffing levels, capabilities?
• Do we have the skillset internally to build, control, and manage an evolving solution ourselves?
• Should we leverage, or bet on the big consumer models, or open-source tech in some way?
• The cost of building or leveraging models at scale?
• How do we control for the big questions? - Security, Privacy, Supervision, Transparency, Legal Exposure, Inaccuracy, Implementation and Maintenance Costs, etc.
• Are there specialized vendors we should consider? What is their strategy, security, capability, flexibility, cost, ROI for our possible use cases?

And finally, can the company afford to sit on the sidelines for long, putting off the learning curve and the possible benefits? This sort of internal debate is healthy, and useful, IF it does not result in a lengthy blockage of progress, or ‘analysis paralysis’.

Companies Can Progress, By Crawling, Walking, Then Running

In our work with organizations in different industries, of different sizes, we have seen and supported a very common formula for success.

• Ask all your questions. But don’t stop. Get moving.
• Find a simple starter use case and goals.
• Absolutely insist on the fundamentals of security, privacy, control, transparency, relevance.
• Develop a proof of concept.
• Engage the business users who have the most to gain.
• Keep humans in the loop. Don't assume the AI is magic.
• Give attention to the new operating implications.
• Adjust the priorities for use cases as you learn.
• Expect and plan for imperfection, with a roadmap of continuous improvement.
• Map out the next projects based on what you’ve learned.
• Enjoy the amazing results!

That sounds complex, intimidating? – more reasons to stop and debate? Actually, each step informs the next and they create momentum. After all, the crawl, walk, run process happens very quickly and effectively in households everywhere!

Some Examples Of Starting Points

Each of these examples are rapid-turnaround projects where the company started with volumes of business documents with essential information hiding in documents, that required humans to read the details to analyze what was there. They achieved rapid ROI, while avoiding all the negative issues that have created so much indecision around AI implementations.

• A workforce management services company processed their own internal employment service contracts as a first step. They evaluated the trends and created a framework for analysis. Now they are able to help all of their clients do the same, optimizing approaches to specialized outsourced talent.
• A commercial insurance brokerage applied generative AI to their insurance carrier health benefit plan documents locally, turning the data into benefit plan spreadsheets for their brokers, automatically. They were able to beat competitors to the sales process at the end of the year. Now they can do it in branches all over the country.
• A property and casualty commercial brokerage processed Loss Run reports and other ACORD forms locked away in an agency management system, to generate a risk assessment of the brokerage’s entire customer portfolio.
• A company implemented a new Contract Lifecycle Management repository. They needed a way to populate all the metadata for the system automatically, instead of spending weeks of manual staff effort.
• A marketing services firm analyzed all their customer contracts, to understand the outlier and difficult terms, and then used that information to develop new proposals.
• A medical equipment services provider enlisted AI to extract key information from Order documents to insure rapid, correct, timely order delivery, with staff providing quality control rather than managing outsourced data entry.

The Docugami Promise

By focusing on the information from your own business documents, starting with a proof of concept, Docugami has found that organizations can START IMMEDIATELY with breakthrough Generative AI, in full confidence and control, trusting the results, to quickly turn the promise of AI into concrete benefits, for the short and long term.