It is difficult not to feel a little overwhelmed by the AI hype machine we see all around us these days. Many technology thought leaders feel strongly that AI will be bigger than the industrial revolution! A thought that is difficult to comprehend but let’s look at the how, the when and the where it may help companies now.
One of the key reasons AI could happen so much faster is not just the pace the large language models are being worked on and compute power thrown at them, but the fact that we are all “pre-prepared” for the outset.
When the internet came along, there was a “tooling up” period that required everyone to get online (be that a modem, a new computer or learning what it actually did). When the smartphone arrived, we all needed to trade in our old Nokias for Iphones and Androids, and that also took some years. With AI, we are already fully tooled up! We have the hardware and the software to run even personal AI bots using our existing smartphones. We’re all already reading and gaining an understanding of what AI,LLM and AGI is.
In the workplace we can see that AI powered software can impact many functions and applications within companies. I believe, as usual, that this will elevate repetitive human jobs to higher skilled ones by the way. A good example of this is Microsoft, with their Office365 product, a $100 billion per annum product with almost 100 million users globally. They were able to add a gpt4 co-pilot into the Office within 100 days of it launching! A far cry from the windows 98 disks.
This is a really good example of how any company can add AI tools on top of existing platforms in record time. This syncs nicely as well with the fast pace of AI we see industry wide.
On the opposite side of things, it’s also important not to think of AI as a “hammer looking for nails”, the technology is not yet mature for some applications and it does not yet work across all areas. When thinking about AI applications, it is vital to think in time and ROI, just like the Microsoft example, where we can add AI products or AI layers onto existing products in a relatively fast time frame and see ROI.
Freight tech could be a very interesting use case for AI, given that the industry has seen an increased speed of digital transformation over the past number of years, but still with a lot of spreadsheet heavy areas yet to be disrupted. AI could move the process years ahead in a matter of quarters.
To offer a practical example, with Ship Angel, we looked at six possible areas where AI could enhance our platform and settled on one for maximum short term impact. We built a 7 pilar ML/AI architecture to convert any shipping rate format into an API without human touch, and got it working in less than ten weeks!
Ship Angel’s Rate Management platform is the first of its kind to provide beneficial cargo owners one single source of truth for their global shipping rates while enriching them with ten key data points including benchmarking, transit time, MQC and more!