Rules of Thumb for AI projects

The 70% Technology Rule of Thumb for AI Projects

by Mark Clark, on June 18, 2020 6:39:07 AM PDT

AI is powerful stuff—but the technology alone won’t create business value. In fact, building good, useful AI with its accompanying technology is really only about 30% of the challenge. Taking advantage of its power is the other 70%. A project needs to both create AI insights and use those insights to move the needle.  

How to Create Business Value Using AI

When planning an AI project, a good rule of thumb to use is the 70% rule. The 70% rule says a successful AI project will consist of: 10% AI algorithms, 20% technology, and 70% business process transformation.

AI project success drivers by Infrrd

The 70% rule of thumb is a good reminder that both the business and technical sides of your company need to work together to successfully transform your processes.

Let’s look at each driver and then see how that applies to a specific client example.

AI > Technology > Transformation

Driver 1. AI

AI algorithms are catching everybody’s eye these days. And for good reason—tasks that once required human intelligence can be executed by a machine using AI algorithms. These algorithms can dramatically alter and improve how work gets done, and that opens up new possibilities. But AI’s sizzle is only 10% of a successful project.

Driver 2. Technology

The technology stack makes up another 20% of what is required to make the AI algorithms work. AI is always integrated into the pipeline of data processing, and into a technology stack needed for the work to get done. 

Driving powerful results requires MLOps, which is the integration of AI into the enterprise IT architecture, power functioning in that solution ecosystem, and operations. For algorithms to create value, they require a technology bridge into the enterprise. 

Driver 3. Business Process Transformation

AI and technology can power big change, but not in a vacuum. Gartner describes AI as a business problem, not a technology problem, for this reason. 

Getting an AI-based solution into production and then transforming the process is 70% of the work. That’s because it requires changing familiar processes and systems, and re-evaluating both how work gets done and people’s roles in all of the steps along the way.

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Creating Business Value Using AI to Improve Insurance Claims Processing

One of Infrrd’s insurance clients processed claim documents that were so complex that it needed skilled staff to extract the data from the forms. The firm had a staff of 90 people doing manual data extraction, which was costing the company $5.8 million a year. 

The client had not been able to reduce or eliminate manual processing with any technology-based solution it tried. The insurer got a recommendation that Infrrd might be able to solve its problem. 

Infrrd showed this firm how to properly use AI to tackle its problem. To create business value, Infrrd’s Intelligent Document Processing solution used AI, technology, and process transformation.  

Let’s see how the 70% rule was applied to help this client transform its insurance claims process.

Driver 1. AI is 10%

With Infrrd's algorithms, the company was able to achieve better-than-human results for data extraction from complex documents. Without the algorithms, the cognitive processing power of a human could not be matched.  

But, while the algorithms are an important part of the equation, these break-through capabilities needed to be paired with technology and process transformation to create real business value (remember we are after business impact, not AI bragging rights).  Using the rule of thumb, we can think of these algorithms as accounting for 10% of the overall solution. 

Driver 2. Technology is 20%

AI algorithms created the breakthrough and did the heavy lifting for this client, but that was only one component of the overall end-to-end data extraction solution. The AI components reside in a technology stack that includes workflow, business rules, security, user controls, management, and various microservices.  

Additionally, the solution is integrated into the insurer’s existing enterprise IT architecture and functions within that ecosystem. Consider that all these technical components, other than the AI algorithms, account for another 20% of the total solution.

The client now had an AI-based solution that automated data extraction and was integrated into the enterprise architecture. The extraction solution enabled the claims process to operate faster, at a lower OpEx, more efficiently, and with agility to scale. 

At this stage, the client achieved a technology breakthrough. It was time to reap the business benefits.

Driver 3. Business Process Transformation is 70%

The final 70% of the solution required the insurer to put AI to work. At the start of the project, the firm had defined how it would transform the claims process once the AI solution was deployed. 

Business process transformation can be considered 70% of the work because to take full advantage of the new capabilities, existing legacy processes, systems, KPIs, incentives, organizational design, and product offerings may need to be changed. 

This client worked with Infrrd to achieve complete process transformation and real business results. As an example, the firm was able to reduce staffing (from 90 to 45 people), reduce the time needed to process a claim, and increase process capacity, without adding headcount.

Client Results Using the 70% Rule

How powerful is the 70% rule? This client’s claims process is now faster, more efficient, and twice as cost-effective on a per-claim basis. This client also achieved an investment payback in three months. 

Want to Use AI to Transform? Know This

To create business impact from AI requires AI algorithms plus technology plus process transformation.  After years of helping our clients create business value using AI, we know the 70% rule of thumb to be a valid principle with broad application. 

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Topics:Intelligent AutomationAI ReadinessBusiness Insights

About this blog

AI can be a game-changer, but only if you know how to play the game. This blog is a practical guide to turning AI into real business value. Learn how to:

  • Make sense of complex documents and images.
  • Extract the data you need to drive intelligent process automation.
  • Apply AI to gain insights and knowledge from your business documents.

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