Do you have an organization-wide AI strategy? Source: Shutterstock

Do you have an organization-wide AI strategy? Source: Shutterstock

Actions speak louder than words: Businesses not using AI to think big

WHILE MOST business leaders are talking about artificial intelligence (AI) and exploring AI-powered applications, not everyone has an enterprise-wide AI strategy.

Think tank and market research giant IDC recently conducted a survey of global organizations of organizations already using AI and found that only 75 percent of them haven’t put plans in place to scale up their use of AI across the organization.

This is perplexing because the same survey also found that half the organizations surveyed see AI as a priority and two-thirds are emphasizing an “AI-first” culture.

“Organizations that embrace AI will drive better customer engagements and have accelerated rates of innovation, higher competitiveness, higher margins, and productive employees,” said IDC’s AI Strategies Program VP Ritu Jyoti.

“Organizations worldwide must evaluate their vision and transform their people, processes, technology, and data readiness to unleash the power of AI and thrive in the digital era.”

IDC’s analysts believe that the primary driver behind these organizations’ AI initiatives were to improve productivity, business agility, and customer satisfaction via automation.

Faster time to market with new products and services was another leading reason for implementing AI.

In today’s market, AI solutions are often easy to access because they’re embedded in most of the top software products — and more affordable as leading solutions are available on the cloud as a SaaS offering.

AI-powered chatbots, for example, that not only use scripted responses but also natural language processing (NLP) to better understand questions posed to them online, is a good example of something that significantly improves customer satisfaction without too much technical nuance.

However, IDC’s survey did reveal some impediments to AI adoption as well.

According to the respondents, the cost of AI solutions, a lack of skilled personnel, and bias in the data were primary factors holding back the implementation of AI technology in their organizations.

While the lack of skilled personnel is a challenge that organizations, academia, and regulators need to deal with together, the cost of AI solutions and the bias in data are easier to resolve.

In fact, with leading technology giants such as Google and Amazon creating intuitive, cloud-based AI capabilities that can be deployed quickly, with a bit of customization, for a variety of purposes, the cost of AI solutions, especially for enterprise-wide use cases, could soon be reduced significantly.

Bias, on the other hand, is a tough nut to crack — especially as algorithms in the world of AI get more complex and transparency in the automated decision-making processes becomes a challenging issue.

According to most experts, the bias in data, for the most part, is what will be the biggest challenge for most enterprises looking to scale-up their AI masterplans.

In the future, as AI gets more commercialized, it is expected that the obstacles to enterprise-wide AI adoption will disappear and organizations will be able to accelerate AI-uptake within the business more creatively.