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Part 2 of 3: Understanding AI’s Application in Industry – Where Academia Comes in

Off-the-shelf AI products and ready-to-use data models work well in simple use cases and business applications. In fact, these solutions help prove the case for AI’s efficacy. There’s a continental shelf where unique workflows and datasets quickly become complex. That’s when AI still needs a lift from academia; professionals with deep experience in data science and machine learning.

There’s a misguided assumption that AI is data science. It’s not (although data is the fuel). To truly understand the complexities of these algorithmic models and to customize them to your business needs, you need someone trained at the forefront of machine learning and AI. No matter how smart or determined your internal team, be cautious. The field is new and the expert talent pool is small.

In our client engagements, we often work closely with what we like to call an “AI Evangelist”, someone who sees the potential of machine learning to improve productivity and has invested time and energy in self-education or even some formal learning around AI. This person, an expert for their industry or department, with critical understanding of our area of expertise, is the key to success. By working hand in hand with this evangelist, our data scientists and AI experts develop real solutions to distinct business inefficiencies.

Successful outcomes are driven by the marriage between academia and industry. This means that any good AI consultancy will employ both PhD-level researchers and strong business leaders with proven track records to drive project direction, scope technical architecture, and see successful implementation through to completion. Tim, our co-founder and Chief Data Scientist, likes when clients bring him an input and an output but want to know how to get in between the two.

Deploying AI and machine learning doesn’t have to cost millions. It doesn’t necessarily require hiring your own senior data scientist, either (whose average annual salary is $136K+ according to Glassdoor, a number that doesn’t account for company overhead). This costly option isn’t optimal for most organizations and department heads. Not least of all because it’s extremely difficult to hire for this role. What’s the alternative?

An AI engagement with a boutique consulting firm can work like a precious instrument for companies and business leaders looking to get ahead of the competition. Rather than costing hundreds of thousands a year, engagements should start in the low tens of thousands, depending on project scope and size. Furthermore, a good consultancy will have dozens of proven use cases and successful real world applications.

Next week we’ll unpack how to deploy unique, streamlined, and affordable AI within your organization. Stay tuned!