A partial view of a businesswoman pushing wooden dominoes while an AI-driven robotic hand prevents the cascading dominoes - AI challenges concept
PHOTO: Shutterstock

Artificial intelligence (AI) is rapidly gaining traction in the enterprise, however, there is still a great deal of resistance to using AI in the workplace. This is very much like what we saw with cloud computing in the early days in which a number of industries were reluctant to jump on board. Recent research from Capterra showed that fewer than one in five business leaders use AI, yet many acknowledge that it's critical for their business.

Finding The Right Technology

The 2018 Capterra survey of more than 700 small and midsize business (SMBs) leaders in the United States found that identifying the right technologies for their business is a top challenge — one in five respondents (19 percent) cited it as their main challenge.

Chabot’s, or conversational user interfaces, for example, are becoming increasingly popular thanks to the personalized experiences they offer consumers. In fact, nearly 65 percent of millennials say they want to use chatbots when engaging with brands. However, less than 30 percent of small businesses in vertical segments such as retail, services, construction and manufacturing are incorporating chatbots. Gartner predicts that by 2019, three times more businesses will use chatbots than used them in 2017. Overall, this demonstrates a sizable gap between needs and SMB investments.

There are some other interesting findings that feed into fears about AI. Here are the notable ones.

  • AI is often portrayed as a stand-alone technology that can replace human colleagues, a viewpoint that both over and underestimates AI's current capabilities.
  • SMBs aren't adopting chatbots fast enough to keep pace with consumer demand.
  • The result is that SMB owners avoid investing in AI that could, if deployed, help their human team members work smarter.

Capterra recommends SMBs include AI in their software evaluation process. Many popular vendors, including Slack (communication), Xero (accounting), and Google Drive (file storage and collaboration) already incorporate AI through features such as auto reply.

Related Article: 7 Ways Artificial Intelligence is Reinventing Human Resources

Why Use AI?

Another conclusion in the report worth noting, though not specific to AI, is that SMBs must adopt new technologies within two to three years if they want to have a competitive advantage. If you wait five to seven years to adopt new tech, you might never catch up to your competitors.

Ram Shanmugam, founder of AutonomIq, said that process automation, computer vision and machine learning are the top three AI tools/techniques that are enjoying widespread adoption within the enterprise. He points out that the early adopters in each industry segment, according to customers, are using AI to create competitive differentiation in the form of:

  • Better customer experience.
  • Higher productivity and efficiency.
  • New solutions that were previously not possible.

However, Shanmugam pointed out that the same kind of conversations with customers revealed a number of barriers for AI adoption, which are deterring enterprises, particularly in situations that are characterized by one or many of the following criteria:

  • Lack of a clear AI strategy.
  • Limited usefulness of data and analytics.
  • Functional silos that prevent the usefulness of AI.
  • Lack of clear ownership or leadership.

Related Article: What Is Explainable AI (XAI)?

AI as a Disruptor

AI will be one of the most disruptive and productive advances in business the world has seen. It is poised to have a transformative effect on consumer, enterprise, industrial and government markets around the world, said AJ Abdallat, CEO of Beyond Limits. It has the potential to assist in medical breakthroughs, improve health and safety, democratize costly services, elevate poor customer service and even free up an overburdened workforce.

But what's really driving the adoption of AI is the new “explainable AI technology,” which has the ability to both arrive at, and explain answers. Conventional AI systems are not explainable. Explainable systems are referred to as black box implementations because they are trained based on data, but cannot explain how they arrive at an answer or solution.

This is a problem for organizations like NASA, for example, which will not implement any system where you cannot explain how the system arrived at an answer as well as an audit trail. “I think establishing trust is important. In industries where the stakes are high, like medicine, energy and finance, people need accurate information. We need to have doctors, engineers and other professionals understand how they got the answer and provide them with that audit trail,” Abdallat said.

Explainability will be critical if AI is to truly benefit society. Explainability can mean many different things depending on the user who requires the explanation. In general, the higher the potential stakes are, the more explainability is required. Cognitive AI can break down silos and bridge the gap between IT personnel and non-technical executive decision-makers, allowing for effective governance, compliance, risk management and quality assurance.

AI is increasingly making its way into the workplace, with virtual personal assistants (VPAs) and other forms of chatbots now augmenting human performance in many organizations. Gartner predicts that, by 2021, 70 percent of organizations will integrate AI in the workplace to assist employee productivity. This development will prompt 10 percent of organizations to add a digital harassment policy.

“Digital workplace leaders will proactively implement AI-based technologies such as virtual assistants or other [natural language-processing] NLP-based conversational agents and robots to support and augment employees’ tasks and productivity,” said Helen Poitevin, senior research director at Gartner.  She warned, however, the AI agents must be properly monitored to prevent digital harassment and frustrating user experiences.

Past incidents have shown that poorly designed assistants cause frustration among employees, sometimes prompting bad behavior and abusive language toward the VPA. “This can create a toxic work environment, as the bad habits will eventually leak into interactions with co-workers,” Poitevin said.

Overcoming AI Obstacles Is a Global Issue

Fujitsu may have an answer to overcoming these obstacles, according to Duncan Tait, senior executive vice president and head of Americas and EMEIA.

Recent research from Fujitsu, entitled Timeline 2030, is a global rather than a piecemeal approach to AI and other disruptive technologies that, according to Tait, presents visions of the potential future by 2030, underlining the long-term impact of the decisions made today and urging timely and coordinated action across global governments, business, education and society as a whole. The trends believed to have the biggest impact on businesses by 2030 are as follows:

  •  70 percent of the world will have internet access/be online.
  •  Automation (including robotics and AI).
  •  Aging population.

In respect to AI and robotics the report reads: “If we are to reap the societal and economic benefits automation presents, we must address the speed of uptake, global investment, skills investment and mindset. By taking a responsible approach to adopting automation we can prevent widespread unemployment and create a complementary equilibrium between the analytical power of AI and the creativity of people.”

If fear of the impact AI will have is a major hindrance to adoption, then a global approach that foresees the disruption is the solution, Tait writes, "Recent research from Fujitsu suggests that levels of uncertainty around the way businesses should plan for imminent technologically-driven change are so high that business leaders around the world favor a coordinated global approach led by intergovernmental bodies and governments."