Transform 2021

Elevate your enterprise data technology and strategy.

July 12-16

Artificial intelligence is proving to be most valuable when it is applied to rote, predictable functions. At first blush, this may not sound like an ideal fit for customer relations management (CRM), but keeping customers happy requires a lot of tedious work.

In today’s increasingly digital world, CRM lives and dies by data — not just the amount of data gathered but the quality of that data, which can only be achieved by cutting-edge analysis and interpretation. But today’s volumes are simply too much for human analysts to cope with (at least, in a timely fashion), so CRM platforms of all stripes are starting to incorporate AI to handle the load.

Bad data, bad decisions

Faulty data management is a key factor in poor customer relationship outcomes, with more than 85% of sales agents citing it as the cause of embarrassing mistakes, according to marketing analysis firm MarTech Series. Upwards of 2.5 quintillion bytes of data are being created every day, 90% of it unstructured, so the mere task of putting all of this data into context is functionally impossible without AI. And AI can be integrated directly into CRM workflows to handle the tedious tasks most people don’t want to do anyway — and usually can’t do without introducing numerous errors. At the same time, AI can be trained to communicate directly with customers, either by text or voice, to address simple questions or easily solvable complaints.

As counterintuitive as it may seem, AI is likely to produce a more personalized approach to CRM than is currently possible. AI can assemble and assess a customer’s digital history — including purchases, emails, and other events — to determine their needs and temperament much faster and more thoroughly than a human representative could, Anzhelika Danielkievich recently wrote on the Keen Ethics blog. This helps resolve problems in a timely manner, and with a higher degree of satisfaction, but it also enables a more accurate representation of brand sentiment to further hone marketing and communication efforts.

In addition, AI can do wonders for much of the behind-the-scenes work of CRM, such as lead scoring, cross-selling, price optimization, and sales forecasting. This information can then be used to improve business strategies, right down to targeted advice to sales reps to guide them through each stage of the sales pipeline.

A friendly voice

The ultimate goal is to provide better customer service, according to software developer Nahla Davies. At the moment, one of the chief complaints aimed at companies large and small is the long wait times at call centers and in email replies. A properly trained AI-driven CRM platform will be able to handle most common queries with little to no delay, sending the more complicated requests to service reps, who should have greater availability. AI will also be able to more effectively communicate with customers over the web, social media, and mobile platforms.

AI can also help people interact with enterprise services in a more streamlined and secure fashion. Davies notes that mobile banking is already pushing software that allows customers to take complete control of their finances, with AI programs constantly monitoring for threats and then pushing out the appropriate updates to security tools like encryption and two-factor authentication.

As with any software, it’s important to note that all AI-based CRM platforms are not created equal, nor are they immune to vendors’ tendency to overpromise and underdeliver. For instance, all the talk about almost humanlike interaction between customers and service bots tends to skip the fact that this level of technology is still a few generations away. Right now, AI bots are being purpose-built for specific use cases, such as data entry and task scheduling.

On the other hand, AI is giving a major and immediate boost to functions like predictive analytics for everything from trend and market forecasting to driving inefficiencies out of supply chains. In the end, enterprise executives should take a hard look at what AI can do best and target it at specific areas where its efficacy can be measured against established metrics.

Perhaps the most important thing to keep in mind when augmenting a CRM with AI is that the technology should be a conduit to successful outcomes, not a barrier. Many people will gladly engage with AI if it provides a quick, simple resolution to their problem. But frustration will mount if the problem is not solved and they can’t get past AI to a human representative.

Likewise, customers will likely be unhappy if they are talking or texting with what they think is human but turns out to be a bot. The use of AI should be made clear up front, and it must be used at the customer’s discretion.

Transform 2021

Elevate your enterprise data technology and strategy.

July 12-16

Presented by Appen

As a rapidly-evolving and innovative industry, AI is a fascinating space to watch. In Appen’s 7th edition of our State of AI report, we provide a snapshot of where the AI industry stands today. Through surveying senior decision-makers on both the business and technical side of companies large and small, we discovered how leaders are finding ways to make AI work in the real world, what they’re prioritizing, and where they still face major challenges. These findings not only paint a picture of a maturing industry, they also serve as a useful resource for AI practitioners working toward their own deployments.

Highlights from the State of AI 2021 report

Finally, organizations are making meaningful progress toward beating the deployment odds, as AI moves from a fringe benefit to a core offering. Success may be more achievable than ever before with the right approach, although formidable barriers remain. To provide a better illustration of what factors are driving the industry, here are several key findings from the report, with commentary on what these may signify for companies in the space:

Increased AI budgets show a maturing industry

AI budgets from $500k to $5M have increased by 55% year-over-year, with only 26% of survey respondents reporting budgets under $500k. Not surprisingly, budget was highly correlated with company size. Respondents from companies with higher budgets were more likely to see themselves as market leaders.

What these increases show is that the AI market is maturing as a whole, bringing foundational changes to the way companies leverage technology for their customers and internally for themselves. A large AI budget is a strong indicator of success, demonstrating the resource-intensive nature of AI (an unfortunately limiting factor for new entrants in the space).

A shift toward maximizing internal processes

More than ever, companies are applying AI to support internal processes for efficiency gains. IT operations were ranked as the top use case for AI, with understanding company data and improving productivity of internal business problems ranked second and third respectively. AI products and services scored much lower, illustrating the major shift toward internal applications.

In these times of economic uncertainty, it’s reasonable for businesses to direct their attention inward toward cost-reduction endeavors. Internal AI initiatives are also less risky in terms of financial investment and brand reputation. With these factors in mind, we can likely expect to see this trend persist as the global pandemic continues.

C-level executives delegate AI responsibility

In past reports, we saw an upward trend of C-level executives becoming more responsible for AI initiatives in their organizations — in 2020, 71% of executives reported having responsibility. In 2021, that trend changed course, with the C-suite delegating to VPs and directors (a shift from 71% to only 39% reporting having responsibility for AI in their organization). We also are seeing technical leaders take on AI leadership roles more so than their business counterparts.

Priority gaps persist between business and technical leaders

Every year, we evaluate the levels of disagreement between business and technical leaders. In 2021, these two stakeholders are aligned in key areas like data diversity, the usage of AI, and external data providers. Yet, gaps remain most significant in ethics (technical leaders rate ethics as more important) and interpretability (more highly-rated by business leaders).

Given that these gaps remain, companies pursuing AI may consider ensuring upfront that all relevant stakeholders are aligned on key priorities for the organization. More often, companies are documenting these priorities in governance frameworks, which helps to create a strong foundation for strategic decisions around ethics, data, etc.

Majority of companies prioritize high-quality data

Throughout the report, respondents cited data as a top priority, with special attention to factors like data security. Companies are finally embracing the fact that data is mission-critical to high-performing AI. As a result, they understand the value of partnering with an external data provider, especially as data collection and preparation remain top challenges. Those that use external data providers (a vast majority of respondents) reported more successful deployments and were 1.5 more likely to claim their company is an industry leader.

COVID-19 continues to accelerate AI development

The pandemic has prompted businesses to connect with customers (and in many cases, remote employees) in more virtual and therefore more technology-focused ways. It’s unsurprising, then, that 55% of respondents report that the pandemic has accelerated their AI efforts in 2021 (17% report no impact either way). Even more companies, especially those of larger size, anticipate that the pandemic will accelerate their projects in the future.

Looking ahead

It’s an exciting time in AI as more companies learn how to successfully launch and scale their AI initiatives. We see organizations operationalizing AI for internal efficiencies, putting trust in technical leaders to carry out projects. We see the impact of the pandemic as the AI space is forced to evolve and innovate in response to new customer demands. And we also see the acknowledgement of the importance of high-quality data in training high-performing AI.

The results of this report suggest that companies are better understanding the priorities and tools they need to overcome barriers and launch AI confidently. Of course, there’s no tried-and-true pathway to success yet, but with these findings perhaps we’re one step closer to identifying the techniques that will get us there.

To learn more, download the full State of AI Report.

Wilson Pang is CTO of Appen.

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