We Need More Chandlers!
OK, so Chandler wasn’t exactly a data scientist (and no Rachel, he wasn’t a “transponster”), but hopefully you get my point – we need a lot more people in data analytics if the new Industrial Revolution is going to happen or we need to make the people we have a lot more productive.
IDC recently estimated that 500 million new AI-driven applications will be needed in the next few years. Given current rates of productivity, we would need hundreds of millions of data scientists and AI application developers to build all of these solutions and, regrettably, there just aren’t that many Chandlers around.
This is the fundamental problem that we at Geminos are setting out to solve – improving the price/performance of AI solution development by >10X. In the mid-term, we will be “Using AI to Build AI” as per our tagline, but in the meantime, our approach can already provide significant improvements and we have a great team of highly experienced data scientists that can deliver solutions with very compelling time and cost to value.
Isn’t Industry 4.0 Already Happening?
Reading the press, it seems as though everyone is implementing AI-driven solutions as part of broad digital transformations that will take them to “Industry 4.0”. The reality is somewhat different.
While it’s true that large companies such as Wal-Mart, Amazon, FedEx, etc. have had successes and in some cases have radically improved their operations or even created entirely new lines of business, the successful use of AI has not yet reached the broader market to the same extent.
A recent report by Cognilytica showed that only 9% of North American companies have multiple AI solutions in operation, with a further 22% having one in operation. The vast majority of the rest have their first project in progress (18%) or are planning one in the next 1-3 years (42%).
Shortage of Talent is the Main Challenge
One of the main reasons why these companies struggle to keep up is the difficulty they have in hiring high quality resources that can deliver effective solutions.
The same report by Cognilytica stated that “Limited AI Skills or Talent” was a showstopper for 13% of all companies and slowing adoption for a further 27%. Our own research indicates that these numbers are significantly higher for mid-sized companies.
Cost is Also a Factor
It’s not just the shortage of data scientists and experienced AI solutions developers; cost is also a factor. Recruitment costs for a team can run to hundreds of thousands of dollars and salaries are often significantly higher than those for existing IT resources. Also, competition for the very best resources is intense and there are many appealing opportunities for the more capable people.
If you opt for outsourcing, major systems integrators (SIs) such as IBM or Accenture are, of course, an option. The challenge with major SIs is those very same expensive data scientists are additionally burdened by SI overhead and typically tied to expensive, multi-year engagements. Also, their best talent will likely be committed to accounts with larger annual billables.
Geminos Can Help
As stated above, Geminos is dedicated to helping you to solve this problem. We’ve accumulated decades of experience in building AI-driven solutions for industrial, logistics and retail customers that have resulted in up to 30% improvements in revenue and/or cost savings. We’re also highly motivated to prove that our approach to building these solutions is significantly more cost effective and less risky than inhouse teams or the major SIs.
If this sounds interesting, you can contact us at firstname.lastname@example.org
About the Author
Stu Frost has 30 years’ experience in founding and leading successful data management and analytics startups. He has raised over $300m in funding and founded/co-founded 31 startups. Successful exits have included IPOs and acquisitions, including one by Microsoft.
In the last eight years, Stu has created and incubated some of the leading companies in the IIoT market, including Maana (IIoT knowledge platform), OspreyData (oil and gas analytics), NarrativeWave (wind farm analytics), ThinkIQ (food traceability) and SWARM (AI agents for IIoT). During this time, he saw the market go from its very early gestation to the point where major industrial companies are starting to make significant, long term commitments to digitization. Through this unique experience, Stu has developed deep knowledge of the market’s needs and how to successfully create and sell key technologies to meet those needs.
His latest company, Geminos Software, has created a platform that is designed to improve productivity of developers building AI-driven analytics by 10X.
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