Cogeco Peer 1: Overcoming barriers to AI adoption
Susan Bowen, President of Cogeco Peer 1, discusses the increasing importance of data-driven artificial intelligence solutions, and how to overcome barriers to its mass adoption.
Whether you consciously think of it or not, data is fast becoming critical to the efficient functioning of modern life. From simple everyday tasks, to complex management systems, in a relatively short amount of time, data technology has transformed our lives beyond recognition.
Data infrastructure is critically important to modern society, creating vast amounts of economic value. With recent developments in data technology, as well as advanced algorithms and super-fast processing, we now have artificial intelligence (AI) that is capable of rapidly learning and adapting from patterns in data.
This acceleration of smart technology has led to AI moving beyond the lab to generating an abundance of interest in the role it can play in mainstream business. However, while many organizations are waking up to the enormous potential of AI, there are barriers to overcome that are causing slow adoption.
For businesses, the promise of AI is the potential to unlock increased productivity, greater profitability and reduced costs. In fact, as AI systems become more sophisticated, research firm Gartner predicts that 70 percent of organizations will have integrated AI to support employee productivity by 2021.
As the demand for AI solutions grows across all industries, among the biggest challenges to adoption for many businesses is talent. Finding the best people, with the right combination of skills and knowledge to put AI to work in a specific industry can feel like a treasure hunt. And, this particular skills shortage further widens the already growing ‘digital skills gap’ within our society. It has been estimated that the digital skills gap alone could cost the US economy an estimated $2.5trn over the next ten years, with at least 2.4mn roles potentially left unfilled during that time.
Further exacerbating the problem is an additional barrier to AI adoption - risk aversion at the C- level. Whether through lack of understanding of the technology itself or an inability to link it with measurable short-term benefits, businesses leaders increasingly risk missing out on valuable opportunities. For many executives, it can be difficult to justify the investment in an experimental AI project, consequently other business opportunities can easily take priority.
Despite these barriers, few problems are intractable, and these roadblocks can certainly be overcome. The technology requirements and knowledge of AI implementation requires not only the right technology, but the right people and processes too.
Businesses should consider a technology partner who not only understands their immediate concerns but also their business objectives, overarching issues and the need for cost-effective technologies. By outsourcing crucial IT infrastructure requirements, businesses can not only reduce costs and avoid risks, but also bring in outside talent and expertise.
Moving forward, businesses should invest in building an AI mindset within the company by preparing employees with the necessary education, ownership, tools and processes they require. According to a research survey of 1,075 businesses across 12 industries, the more that companies embraced employee involvement in AI design and deployment, the better these initiatives performed.
In a recent article in the Harvard Business Review, AI experts warn about the perils to businesses who wait too long to adopt AI. They express by the time a late adopter has done all the necessary preparation, earlier adopters of AI will have taken considerable market share and will be able to operate at significantly lower costs with better performance.
As Charles Darwin once said, “it is not the strongest of the species that survives, it is the one most adaptable to change”.
New technologies will continue to emerge and develop at rapid rates, and as such, AI is inevitable and will consequently reveal its own winners and losers. Those inclined to champion AI and new technologies will enjoy the competitive advantages that they could only dream of today. This future is one of positivity, collaboration and innovation.
How changing your company's software code can prevent bias
Two-third of tech professionals believe organizations aren’t doing enough to address racial inequality. After all, many companies will just hire a DEI consultant, have a few training sessions and call it a day.
Wanting to take a unique yet impactful approach to DEI, Deltek, the leading global provider of software and solutions for project-based businesses, took a look at and removed all exclusive terminology in their software code. By removing terms such as ‘master’ and ‘blacklist’ from company coding, Deltek is working to ensure that diversity and inclusion are woven into every aspect of their organization.
Business Chief North America talks to Lisa Roberts, Senior Director of HR and Leader of Diversity & Inclusion at Deltek to find out more.
Why should businesses today care about removing company bias within their software code?
We know that words can have a profound impact on people and leave a lasting impression. Many of the words that have been used in a technology environment were created many years ago, and today those words can be harmful to our customers and employees. Businesses should use words that will leave a positive impact and help create a more inclusive culture in their organization
What impact can exclusive terms have on employees?
Exclusive terms can have a significant impact on employees. It starts with the words we use in our job postings to describe the responsibilities in the position and of course, we also see this in our software code and other areas of the business. Exclusive terminology can be hurtful, and even make employees feel unwelcome. That can impact a person’s desire to join the team, stay at a company, or ultimately decide to leave. All of these critical actions impact the bottom line to the organization.
Please explain how Deltek has removed bias terminology from its software code
Deltek’s engineering team has removed biased terminology from our products, as well as from our documentation. The terms we focused on first that were easy to identify include blacklist, whitelist, and master/slave relationships in data architecture. We have also made some progress in removing gendered language, such as changing he and she to they in some documentation, as well as heteronormative language. We see this most commonly in pick lists that ask to identify someone as your husband or wife. The work is not done, but we are proud of how far we’ve come with this exercise!
What steps is Deltek taking to ensure biased terminology doesn’t end up in its code in the future?
What we are doing at Deltek, and what other organizations can do, is to put accountability on employees to recognize when this is happening – if you see something, say something! We also listen to feedback our customers give us and have heard their feedback on this topic. Those are both very reactive things of course, but we are also proactive. We have created guidance that identifies words that are more inclusive and also just good practice for communicating in a way that includes and respects others.
What advice would you give to other HR leaders who are looking to enhance DEI efforts within company technology?
My simple advice is to start with what makes sense to your organization and culture. Doing nothing is worse than doing something. And one of the best places to start is by acknowledging this is not just an HR initiative. Every employee owns the success of D&I efforts, and employees want to help the organization be better. For example, removing bias terminology was an action initiated by our Engineering and Product Strategy teams at Deltek, not HR. You can solicit the voices of employees by asking for feedback in engagement surveys, focus groups, and town halls. We hear great recommendations from employees and take those opportunities to improve.