Digital transformation is driving many companies to turn to cutting-edge technology, artificial intelligence (AI) and ultra-high-performance algorithms to improve their productivity, and adapt to the new realities of their market. What challenges are holding them back, and how can we help them overcome them?
Several fields of application
So far, the benefits of robotization have been felt most acutely in the manufacturing sector. But automation also has applications in many other fields. Think of the legal sector, where algorithms are already being used to research case law, using software that targets extracts of interest based on key words; or the largest of industries, agriculture, where more and more cutting-edge technology is being integrated into farms to manage soil, pesticides, livestock, etc.; or the catering sector, for order-taking and deliveries; or any company’s administrative department.
And yet, although SMEs are increasingly aware of and eager to seize the opportunities offered by robotization and AI, some find their ardor held back by the lack of internal structure and budget they have to equip themselves with the best devices for processing and leveraging data. And when entrepreneurs have the means to achieve their ambitions, it’s doubt about the return on their investment that makes them postpone their project: will it be worth it? Are we really going to compensate for the lack of manpower and improve productivity? Or make a hole to plug another, and go into debt? For AI solution developers, the answer is simple: you have to break the kernel to get the kernel.
The NUMERIA program to meet 3 types of challenge
To better understand and identify the type of challenges companies face when launching an artificial intelligence project, we can refer to the Centre de Recherche Informatique de Montréal (CRIM), which has identified three categories of issues: “challenges related to data, financial resources and skills”.
To help Quebec SMEs carry out their first AI project, and put in place a proprietary data strategy, CRIM is offering the NUMERIA program, a three-part program that directly addresses these issues.
“When we survey managers and owners, what we often hear is that access to capital is not the biggest obstacle to innovation. The problem is that they don’t know who to find to help them, or how to go about it…” – Luc Sirois, Quebec’s Chief Innovator.
Challenge 1: Demystify AI and its value to business
“How can artificial intelligence help me achieve my goals? What would be the added value for my company? How much can an AI project cost? What are the prerequisites for getting started?” These are the questions NUMERIA’s experts aim to answer in a precise and specific way for the companies they support in the integration process.
“When we survey managers and owners, what we often hear is that access to capital is not the biggest obstacle to innovation. The problem is that they don’t know who to find to help them, how to go about it… In Quebec, we’re blessed by the amount of capital available to us. We’re privileged. The challenge is to find the who and the how,” explained Quebec’s Chief Innovator, Luc Sirois, during our September 30 C+ Clair program on agtech (technological tools designed to improve the daily lives of farmers).
In another C+ Clair program, produced last week in partnership with Prompt Catalyst on the theme of cybersecurity, our guests argued that investment in technological solutions should be proportionate to the dangers a company would face if it didn’t protect itself.
“When we talk about return on investment when it comes to data backup, given that an organization’s resilience can be at risk, and that this can lead, in some cases, to bankruptcy due to ransomware, should we really be talking about return on investment? The viability of the company is at stake. When you work with technology and the web, and have data to protect and safeguard, you need to consider your risks, understand the type of data you need to preserve, and apply the appropriate means to do so. Investment must be measured against the risks, which are increasingly materializing”.said Marcel Labelle, President and CEO of CyberEco. “Who will talent want to emancipate itself with, if our organizations are not resilient and cyber-protected? Regardless of the investment required, it’s all about the value of the organization and its products,” added François Bédard, Senior Development Officer at the Digital Identification and Authentication Council of Canada (DIACC).
Challenge 2: Developing skills
NUMERIA also offers customized training in the form of mentoring to meet the challenges posed by labor shortages. “NUMERIA’s experts transfer their knowledge and know-how to an identified resource and support them in acquiring the knowledge they need to carry out a practical project. At the end of the project, this person will contribute to bringing AI to life in your company”, says CRIM.
Challenge 3: Adding value to data
NUMERIA also proposes to help entrepreneurs better understand the state, quality and quantity of the data they will need to be prepared to manage as they set up their artificial intelligence project. “Do they require more preparation? What do you need to put in place to get there? NUMERIA helps you better understand the state of your data to maximize the likelihood of success for your AI project.”
According to Silicon.fr, an IT project management specialist, “Companies have also realized that having a data scientist (a scientist or data specialist) is not the answer to the problem of getting value from their data. This is partly due to a lack of understanding of the environment surrounding the data. A data scientist may understand the data, but not its purposes, environments or business applications. Let’s take the example of a marketing department working on implementing AI to accelerate its web ROI. The data scientists will design and implement the algorithm without taking into account this specific environment and its behavior; since the website takes much longer to load than the algorithm, the association doesn’t work.”
The key is to understand data in a context that targets the specific challenges of your industry and type of activity, in order to better leverage data and maximize its positive impact on your business.
Article by Chloé-Anne Touma published on CScience on November 7, 2022.
Image credit: Chris Liverani, Unsplash
