While the benefits of implementing artificial intelligence (AI) and machine learning into a business are reasonably clearly understood, there are still some impediments in the way.

In a recent LogMeIn report, entitled Transforming the Frontline of Customer Engagementthe challenges organisations face when applying AI and machine learning were addressed directly.

The biggest overall challenge is managing organisational change, according to the report. The more senior the executive, the more likely they are to express concern about software and data integrations.

An executive working as Head of Digital & Customer Care in the retail sector said, “Everyone is working towards an integrated system.”

The days when agents were expected to jump between systems running non-integrated software are passing. This still exists, but it’s viewed as untenable.

Instead, the goal is to be able to integrate tickets from social media, email, phone calls and other channels through a single portal.

Our experts stressed that technologies such as machine learning, AI and automation are enablers — not replacements.

Luke Shaw, Head of Ecommerce at Sigma Healthcare, said there may be “areas where company leaders are overestimating the impact of machine learning and AI, at least as it’s applied at the moment.”

Another misunderstanding is the amount of work required. The reality is it takes a huge amount of human input to make these technologies work in the way that companies want them to, according to an executive.

They said, “Obviously, the keywords with machine learning and artificial intelligence are ‘learning’ and ‘artificial’. You do need to teach these technologies the nuances of your particular business and your particular customer base in order for them to deliver the results you want.”

The pace of change is accelerating, and often the workforce is left playing catch-up. This can raise issues around compliance and governance, and even basic ethics.

The executives quoted in the report said some leaders may underestimate the requirements to implement Maxine learning and AI at the enterprise level. You do still need team members that will help train the technology and monitor for areas of improvement.

There is also the issue of a shortage of talent to help implement AI. Sharon Melamed, Managing Director at Matchboard, said it’s all well and good for the C-level to set a mandate for “AI-first” or push for more AI initiatives, but there is often a shortage of talent to implement this vision.

“Technology has moved fast and the workforce is playing catch-up, and there’s lots to think about along the way in terms of ethics and governance.

“Some leaders may under-estimate the manpower required to launch and successfully operate an enterprise-grade chatbot, for example, thinking it’s just a case of buying software. It’s not. You need UX and conversation designers, marketing, IT, analytics and project management resources, just for starters.”

About this author

Athina Mallis is the editor of the Which-50 Digital Intelligence Unit of which LogMeIn is a corporate member. Members provide their insights and expertise for the benefit of the Which-50 community. Membership fees apply.

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