Deloitte has officially published the results from its latest report named How AI is Revolutionizing Restaurants, which was designed to assess AI adoption, what is driving value, perceived challenges, and organizational readiness to scale AI effectively.
Going by the available details, this report reveals that AI investment and adoption differs across the industry due to an interplay between operational focus, customer-facing innovation with back-of-house transformation, and high ambitions with organizational readiness.
“As the restaurant industry appears to increasingly embraces AI, the journey to full-scale transformation is still a work in progress. Leveraging AI to create personalized experiences and deeper connections with consumers can be an effective strategy. However, to unlock AI’s potential, leaders will likely need to balance innovation and operational discipline, strengthen governance, and address capability gaps to help optimize operations, boost margins and future-proof their business,” said Evert Gruyaert, restaurants and food service industry leader, Deloitte.
Talk about the given lowdown on a slightly deeper level, we begin from the fact that, when questioned regarding how they expect their organization’s investment in AI technologies to change in the next fiscal year, more than 82% of respondents would go on to report how their AI investment is likely to increase, whereas on the other hand, only 2% expect a decrease.
Next up, a contingent of 60% respondents deemed enhanced customer experience as one of the top three benefits they hope to achieve through AI efforts, followed by improved restaurant operations (36%) and enhanced loyalty programs (31%).
Another detail worth a mention is rooted in a faction of respondents who expect AI to strengthen their digital marketing efforts (26%), optimize food prep and waste management (25%), enhance crew experiences (21%), and help them develop new products and concepts (20%).
Almost like an extension of it, respondents from casual dining restaurants expected to achieve a significantly greater benefit in enhancing customer experience (60%) compared to those in the quick service, fast casual and café segments (48%).
Markedly enough, the perception around AI was also found to differ region-to-region. You see, when assessing AI’s potential to enable a more positive customer experience, respondents in the U.S. and Europe were found to be more optimistic than their counterparts in Asia (62% of U.S. and 59% of European respondents noted it as a top three benefit, compared to 42% in Asia).
Moving on, both brand and operators surveyed would go on to claim that their AI investments are already generating a high impact today in the context of customer experience (52% of brands, 84% of operators) and inventory management (35% and 25%), among other areas.
Joining them would be a share of 63% respondents who enjoy a better customer service, thanks to the implementation of AI. Given its CRM potential, around 26% also said they are engaged in customer experience pilots or other forms of limited implementation.
Apart from that, inventory management emerged as the second most-common use case, considering an estimated 55% of those surveyed reveal using AI for that purpose on a daily basis, while another 25% say they are actively testing out such applications.
Having said so, there remains an indication that a second wave of AI deployment will have customer loyalty and employee experience as its chief flag bearers. We get to say so because implementation stands at 70% for these two opportunity areas (including daily use and pilots).
Looking past the second wave, a third wave is likely to include leveraging AI in food preparation and new product development. Both applications are being used or tested in these areas by half or less of respondents today, but they also boast the highest readings when it comes to planning and development.
Now, turning our attention towards some of the challenges that threaten to derail AI’s smooth adoption, they include managing risk around AI technology and identifying use cases emerging as one of the topmost concern for organizations (48%). This is closely trailed by lack of talent or technical skills (45%).
When considering the risks related to AI implementation, intellectual property issues (20%) and misuse of client/customer data (16%) also made frequent appearances throughout the response intake.
