Despite corporate enthusiasm around generative AI, business leaders are still nervous about incorporating this into their operations and feel there are many challenges ahead, not least around how best to begin.
Two global studies - one by Workday, the other by Salesforce - provide useful insight into how this is reflected across the HCM and Financials, and Sales and Service sectors respectively.
Workday polled 1000 companies from around the globe for its Insights on Artificial Intelligence in the Enterprise 2023 report. It found that more than 90% of respondents - HR, IT and finance professionals - have already invested in AI, with 99% believing there are real business benefits to be had from using such tech.
Those who have deployed some form of AI or ML [Machine Learning] are already experiencing tangible ROI across many use cases with the overwhelming majority of respondents, 80%, believing that AI can help employees work more efficiently and make better decisions.
Use cases among finance respondents include improved forecasting, automating non-strategic tasks, scenario planning and risk and fraud detection. Among HR respondents, use cases include recruiting and applicant tracking, business analytics, skills assessment tools, skills management , learning management and talent management.
Across all Workday respondents, the top benefits among those already using AI were better decision-making (41%), higher levels of productivity (38%) and automating business processes (35%). Some 34% of respondents see application in re-skilling/up-skilling employees, while 33% are looking to see reduced headcount and hiring costs.
Meanwhile Salesforce surveyed over 2,000 sales and service professionals as part of its Generative AI Snapshot Research Series. Some 61% of sales people believe generative AI will help them serve customers better, while a similar percentage reckon it will help them to sell more efficiently. Among service professionals, nearly two-thirds (63%) predict generative AI will help them to serve customers faster.
On the face of it, such levels of optimism appear to be justified. Among those respondents who are actually already using AI tech, 84% of sales people and 90% of service professionals report positive results.
In terms of the functions generative AI is used for, basic content creation comes out on top for sales people (82%), followed by market data analysis (74%) and automating personalized sales communications. For service professionals, basic content creation again comes out on top along with personalizing service communications, both on 68%, following by better automation of customer service comms.
But, that said, adoption rates remain low - 35% of sales respondents, 24% of service. That’s considerably lower than some other business functions. For example, Salesforce’s research cites 51% of marketers using generative AI. That gap looks likely to continue. In terms of intent, a further 20% of sales and 15% of service respondents plan to adopt generative AI, compared to a further 22% of marketing professionals.
The problem is?
So, what’s the blockage? Both Workday and Salesforce’s data indicate some common themes, including skills shortages and concerns around ethical use and trust.
Some of the Workday survey respondents are very nervous about the impact of AI on their workforce. While nearly half of them, 45% believes that AI and ML will benefit workers, improve workloads and create new career opportunities, 43% are more cautious, expressing worry about AI leading to unemployment. A major concern revolved around a lack of skills, with 72% of respondents saying their organization lacked the necessary skills to implement AI across the enterprise.
Nearly half of respondents said security and privacy concerns are the main barriers in implementing AI in their organizations. Reliability of data is the top concern for many - including but not limited to the hallucination factor - with 77% citing this as an issue, while 48% say that security and privacy are barriers to AI implementation. Currently only 29% are confident that AI is being applied ethically, although more than half of them think this will improve in the next five years.
Across Salesforce respondents, there are similar concerns. Among sales respondents, over half (53%) admit they simply don’t know how to get the most value out of generative AI, while 49% feel they don’t know how to use the tech safely in the workplace and 47% don’t know how to use it ‘effectively’. For service professionals, those same concerns are mirrored at 60%, 55% and 54% respectively.
There are career concerns here as well, with 48% of service and 39% of sales professionals worried about losing their jobs if they don’t get to grips with how to use generative AI properly. But how will they gain the necessary skills? Some 63% of sales people expect training and learning opportunities to be provided by their employer, with 57% of service professionals making the same point. Sadly, that looks pretty much aspirational at the moment, with 67% of sales and 64% of service respondents saying they’re not getting any such training.
And, finally, the majority of both Workday and Salesforce respondents are worried about giving up too much decision-making power to AI. An overwhelming 93% of Workday users say they think it is critical that there continues to be human involvement, while 56% of Salesforce counterparts have similar concerns.
It’s interesting to map those poll findings back to the users who took part in the recent Josh Bersin Company’s Irresistible conference. One of the speakers at the conference, Chief People Officer at Mastercard, Michael Fraccaro told the conference that in one implementation Mastercard had increased employee productivity by 87% using an AI-based scheduling tool. In another, the company has ramped up its ability to match employee skill sets with different project requirements, leading to big gains globally in its employee mentoring schemes.
Mastercard set up an AI governance steering committee composed of business leaders from throughout the company to deal with these sorts of challenges, which focuses on trust, data, data privacy and security and who owns the data.
As with all systems the quality of the data being used will have a big impact on the effectiveness of AI platforms, and 77%of the respondents to the Workday survey felt that this could be a large stumbling block for their organizations. Having an overlying steering committee, like Mastercard has, that looks at data integrity is one way of overcoming this issue.
Meanwhile Tracy Franklin, Chief Human Resources Officer at Moderna, who was also speaking at the event, said her company, which has 4000 employees, uses enterprise wide AI training to solve this problem. The company set up its own University, which has an AI Academy to make sure it gives staff the skills they need.
So, from a user perspective, there are ways around the concerns and blockers to adoption that both sets of survey results surface. From a vendor perspective, it’s clear that Workday and Salesforce leaders get the problem. Carl Eschenbach, Co-CEO at Workday, recently told the Bank of America 2023 Global Technology Conference:
Now, when it comes to generative AI and ChatGPT, everyone's like, ‘Are there use cases?’. We are exploring different use cases that we think could be very valuable. But that's all data that's coming from the internet. That's all data that's probably not highly curated like we are. But we do see use cases around anomaly detection. We see it as a personal assistant. As you're logging into Workday, maybe there's some personal assistant things that you can do. And then we also think there's some mundane tasks that people are doing today that we can leverage that technology for going forward. But we think we're in a good position. We're leveraging it. We've been leveraging it. We'll continue to explore more use cases.
I talk to so many leaders and they're all so excited. They're excited. They can see the benefits. They can see the horizon, they can see the future. But guess what? They're cautious. Very cautious. And why is that? Well, because there is an AI trust gap. Every company wants to embrace this. In fact, for many it is the number one priority. But your customers are not so eager and that's because less than half of them trust companies with their data. And herein lies the challenge.
One last point of note - the genie is firmly out of the bottle! Circling back to the Workday study, 80% of decision-makers now believe that AI is required to keep their businesses competitive. Even those who are worried or feel there are big barriers to AI implementation in their enterprise, know that they are still going to have to get their heads around it. Over 80% said that their level of investment will at least stay the same or increase in the next 12 months. So, there may be challenges ahead - but they can't be avoided if they're going to be turned into opportunities.
(Additional reporting by Stuart Lauchlan)
(Updated a day after publication with minor edits for clarity).