Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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SAP launched SAP Business AI and said it will embed generative AI throughout its applications as it made the case that enterprises should trust the ERP giant with making business processes more efficient.

Speaking at SAP Sapphire in Orlando, CEO Christian Klein said SAP's mission is to make businesses more agile with generative AI as well as process mining and other tools. "No company can afford to run in silos," said Klein. "Back to standard is key to continuous integration and improvement." SAP's main pitch to CEOs, CFOs and CIOs is to integrate into SAP's portfolio and standardize on its data model. 

The software giant outlined 15 new business AI capabilities and use cases while touting customers such as Unilever and Pfizer and partners such as Google Cloud and Microsoft.

"AI will have a tremendous impact on our private and business lives," said Klein, who made the case that AI embedded in the SAP platform will increase productivity and change the way people work. "Our software will be able to answer any business related question and show you how to improve."

In the big picture, SAP is combining generative AI and large language models (LLMs) with its business process knowhow as it aims to make the case that its ERP base is the business performance management platform. SAP's reach is extensive when it comes to business processes. For instance, SAP announced generative AI plans to address multiple use cases including job description and interview question generation via SAP Success Factors, a digital assistant for CX and SAP Signavio Process Manager with process model generation and documentation.

Other use cases for SAP Business AI included finance, sustainability, transportation, warehouse management and procurement as well as sales order auto-completion in SAP S/4HANA Cloud.

The barrage of news from SAP landed a day after it extended a partnership with Microsoft. The two companies will integrate SAP SuccessFactors applications with Microsoft 365 Copilot and Copilot in Viva Learning along with Microsoft's Azure OpenAI Service. SAP has also formed partnerships with Databricks and Data Robot as well as Google Cloud integrations for SAP Datasphere. See: Business process automation platform debate about to heat up

Constellation Research analyst Doug Henschen said:

"Staying out of the LLM game is a practical and realistic approach, and one that competitors including Salesforce are also following.  SAP delivers what it’s calling “Business AI” by using its intimate knowledge of business processes to apply the AI tech in intelligent, value-driving ways."

Among the announcements:

• SAP Extended Warehouse Management is getting intelligent slotting capability that uses AI to suggest how to optimize warehouse organization as well as stock and replenishment processes.
• SAP Transportation Management application will get SAP's document processing with generative AI. Generative AI will be used to automate manual checks of goods, receipts and delivery notes. This capability will be available in the fourth quarter.
• SAP Business Network will embed AI with intelligent invoice conversion to make it easier for procurement teams to add new suppliers, extract data from invoices and map data. SAP Ariba Buying will also get AI to simplify processes.
• SAP Customer experience will get SAP Digital Assistant, currently in alpha, to use generative AI to provide sellers and support teams insights.
• SAP S/4 HANA Cloud will get built-in-support with live recommendations from SAP support teams and enhanced by AI. This feature is expected in May to July as it rolls out across the product line.
• SAP Signavio Process Manager will use generative AI to identify recommended process models and KPIs. Availability will be later this year.
• SAP Predictive Replenishment will use AI to calculate and order products automatically to optimize inventory levels and availability for retailers. SAP Intelligent Product Recommendation will be aimed at manufacturing customers to streamline quotes, opportunities and orders.
• SAP SuccessFactors will use AI to improve talent intelligence and provide a consolidated view of skills, cost and availability across an enterprises workforce.
• SAP announced an update to SAP Sustainability Footprint Management for carbon tracking and the SAP Sustainability Data Exchange, which will enable partners to exchange standardized sustainability data.
• SAP Business Network buyers will be able to select vendors based on sustainability ratings via a partnership with EcoVadis.
• SAP Business Network will add supplier insights as well as streamlined integration, marketplace catalogs, lead matching and enhanced company profiles. Henschen said SAP's sustainability efforts mark "good progress on improving the fidelity of sustainability data to match that of financial data." He added:
• "It’s not just about reporting. Also required is planning and scenario-modeling capabilities that take into account dynamic and changing conditions. If companies are to make and keep carbon-reduction targets, they need to be able to look at the costs and business impacts of traditional energy and sourcing choices versus various alternatives."
• SAP Business Network for Industry are prepackaged packs focused on supply chain collaboration use cases starting with industry and implementation best practices. The first rollout is focused on high tech, industrial manufacturing, CPG and life sciences. SAP CX will also get accelerators to help retail, CPG, automotive and utilities industries to improve experiences.
• Taulia, a working capital management software provider acquired by SAP, is now integrated into SAP Business Network.
• SAP Category Management will be available in August 2023 and include procurement pros with market and commodity intelligence, category management and insights for strategy as well as potential supply chain issues.
• SAP Blockchain Business Connector, which features smart contract management and automated workflows, will launch in beta.
• A series of integrations across SAP applications focused on processes including quote to cash, consumption revenue management, Signavio Process Explorer and other areas.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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C3 AI CEO Tom Siebel said generative AI is about way more than chat and enterprises are likely to use the technology more for enterprise search. "We're using these large language models to basically crawl the enterprise," he said.

Speaking on the company's fiscal third quarter earnings call, Siebel outlined his take on generative AI as well as the benefits of incorporating it into the C3 AI platform so customers can use it for enterprise search. C3 AI's plan is to integrate large language models and generative free trading transformers into the company's platform.

He said:

“By combining the utility of the C3 AI platform, predictive analysis enterprise search, natural language processing, generative pre-trained transformers and reinforcement learning, we have developed a new and novel technique to fundamentally improve the human computer interface for enterprise applications.

This is kind of a non-obvious use of generative AI. This is not about chat, okay? This is about enterprise search. And we believe that this invention represents a breakthrough development that will dramatically facilitate the ease of use and explainability of enterprise AI applications. In addition to providing users immediate, highly controlled access to potentially the entire body of data and information systems within an enterprise, be it Dow Chemical, the United States Air Force, Shell, whatever it may be.”

Siebel added that C3 AI generative search will be embedded into the C3 platform and applications with general availability this spring. Siebel explained that C3 AI has been working with generative AI models since 2020 due to a request from the Department of Defense, which wanted enterprise search that could answer multiple questions from sources as wide ranging as satellite coverage to supply chain status to diversity goals to slides.

He said generative AI also enables DoD to drill down into data via chat and natural language processing. The key point though is that "the chat universe that you know about is only the information content of the enterprise where it was installed." Siebel said C3 AI's architecture enables it to use new engines as needed.

Siebel acknowledged C3 AI is still working on scoping the monetization opportunity for generative AI but will increase usage of the platform.

C3 AI reported a third quarter net loss of 57 cents a share on revenue of $66.7 million. C3 AI's non-GAAP loss was 6 cents a share. The company projected fourth quarter revenue between $70 million and $72 million and guided toward sales between $264 million and $266 million for fiscal 2023.

Other takeaways:

• C3 AI is currently moving to a consumption-based pricing model with more than 290 qualified pilots in the pipeline.
• Google Cloud has become a key partner with the combined teams pursuing 291 enterprise opportunities for joint solutions.
• AWS and C3 AI are pursuing 75 new deals with six agreements closed in the third quarter.
• Siebel added that C3 AI and Microsoft Azure closed a deal "with a super major U.S. energy company."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Process mining is being used to automate multiple processes in finance and supply chain and driving real bottom line value, but Bloomfilter is betting that the technology can revamp the software development lifecycle.

In an interview with DisrupTV, Andrew Wolfe, co-CEO of Bloomfilter, and Erik Severinghaus, co-CEO & co-founder of Bloomfilter, outlined how process mining can be used for the software development lifecycle. Bloomfilter recently raised $7 million in seed funding.

Process mining has been the domain of CFOs and CEOs and continuous improvement teams. Process mining takes logs from enterprise systems to show how work is actually done (compared to how it works on a whiteboard), and companies can make processes such as accounts payable, accounts receivable, order-to-cash, hire-to-retire and logistics more efficient. Since many of these processes revolve around real cash savings enterprises can drive top line and bottom line returns.

Software development has been a different animal, said Severinghaus. "Anybody that oversees and manages a complicated business process knows that there's a ton of waste and inefficiency," he said. "The hard part is always figuring out where that is so that you can root it out and make it more efficient."

Severinghaus added:

"The product development side has always been too hard of a challenge since you can't just go take a typical process mining tool and connect it into the various different systems. There's are a dozen different systems along the product development roadmap. You have everything from Figma up front where you're doing design all the way to Jira. There are different tools across the entire lifecycle to stitch together."

The good news, said Severinghaus, is there is a lot of data to analyze, but it has to be normalized and focused on product development. Bloomfilter has a few patents with more in the works for product development process mining.

Wolfe said there's a big opportunity to automate software development processes. In software development, the typical analytics are lagging indicators such as velocity. "What's missing is why you got there. You may know velocities but don't know where you're going or how you got there," said Wolfe, who added that process mining can enable you to have conversations to better manage sprints. "What we find is a lot of people we talk to are tracking processes in Excel. Some are using PowerPoint. I've seen some amazing Mona Lisa level spreadsheets."

Software development has had a limited picture across the entire process across Figma, product board, Jira, GitHub to AWS. "The indicators are too lagging to make any kind of strategic decisions," said Wolfe, a Business Transformation 150 alum.

Ray Wang, CEO of Constellation Research, asked Severinghaus about tips when considering process mining for software development. He outlined the following:

• Drop the fixation on developers. Severinghaus said the first question Bloomfilter gets revolves around engineers and whether they're working multiple jobs. "There's an obsession that these really expensive developers are just screwing around and that's the reason software isn't getting built," he said.
• Focus on the overall software development life cycle. "We show our clients over and over again that developers are a small piece of the software lifecycle," said Severinghaus. "You may have amazing developers sitting downstream from terrible requirements. It doesn't matter how great and fast developers code or how much AI you apply if the requirements aren't right."
• Know the processes before hiring more engineers. Hiring 10 more engineers won't do you much if your software development process is hung up in QA. "Let's say you create 100 applications a day, but you still have to test them to make sure they're valid and you still have to deploy them," said Severinghaus.
• Beware scaling bad code. AI can speed up the software development lifecycle and deployments, but without a holistic process approach enterprises may just scale bad code at a speed humans can't comprehend, said Wolfe. You have to attack the bottlenecks but keep a holistic view.

Constellation Research analyst Liz Miller asked Bloomfilter's co-CEOs whether they were going to apply process mining to other art-meets-process disciplines like marketing. The short answer is no, but clearly there's a market to apply process mining beyond the usual finance processes.

Here's the full episode with the Bloomfilter interview starting at the 22 minute mark. 

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Generative AI is the question of the day on many earnings conference calls, but the approach to leveraging the technology depends on the industry. Here's a look at how Bank of America, Airbnb, Lemonade and Deutsche Telekom are thinking about generative AI.

Bank of America CEO Brian Moynihan: Generative AI needs more transparency

With existing investments in its ERICA natural language AI, CEO Brian Moynihan needs more transparency before fully leveraging ChatGPT and other generative AI technologies. That approach shouldn't be too surprising given banks are highly regulated.

Speaking on Bank of America's first quarter earnings conference call in April, Moynihan said the bank started working on ERICA, a predictive Q&A bot, years ago. The bank created its own language for ERICA and deployed it. The catch is that ERICA was only looking at Bank of America systems without third party data.

"Because ERICA is captive to our data, where it's just looking at our systems, finding information and giving to clients it is really a service capability," explained Moynihan. "We've also taken ERICA internally and applied it to help us do work and we've seen it have those benefits."

He added generative AI can improve computer coding productivity and content creation as well as analytics. However, Moynihan said transparency is going to be an issue if you're integrating your corporate data with generative AI.

Research: Microsoft Shifts Coding From Typing to Language With ChatGPT

"The reason why a lot of it stopped in our industry and other industries was, it wasn't clear how it worked. It was your data and the outside world's data and how it would interact and pull stuff out and we have to be careful with that," he said. "We have to understand how the decisions are made, and, frankly, follow the laws and rules and regulations on lending."

"We understand the value of it, but we will carefully apply it and we see a great value. I don't think it's a great value in the next month, but in the overall sense, it will help us continue to manage the headcount down which we've been doing this quarter. This management team started with this company in 2010 with 285,000 and 300,000 people working here and we're running the same size company with 216,000 people or bigger company doing more stuff and that's been aided by digitization."

Airbnb, CEO Brian Chesky: All about the tuning

Chesky said generative AI may be as big of a platform shift as the Internet was. The competitive advantage will be for the companies that take a base model and uniquely tune it.

Chesky said on Airbnb's first quarter earnings call:

"All of this is going to be built on the base model. The base models, the large language models, are like major infrastructure investments. Some of these models might cost tens of billions of dollars towards the compute power. And so, think of that as essentially like building a highway. It's a major infrastructure project. And we're not going to do that. We're not an infrastructure company. But we're going to build the cars on the highway. On top of the base model is the tuning of the model."

He said the tuning of the model will be based on the customer data you have. When the base model is combined with customer data then there's a lot of innovation.

"I think that going forward, Airbnb is going to be pretty different. Instead of asking you questions like where are you going and when are you going, I want us to build a robust profile about you, learn more about you and ask you 2 bigger and more fundamental questions: who are you? And what do you want? Think of us with AI as building the ultimate AI concierge that could understand you."

MARKET OVERVIEW: Analytics and Business Intelligence Evolve for Cloud, Embedding, and Generative AI

Lemonade co-CEO Shai Wininger: Integration is easy if you have existing AI stack

Lemonade is a digital insurance company that has been using machine learning and AI for years. It uses models to predict losses and risk down the zip code as well as each discrete home it insures. The goal for the company is to have true precision in pricing and underwriting.

"Lemonade was built as a tech-powered insurance company. We were the first to provide customers with human-like chat-based experience that works 24/7 and handles all of our direct sales," said Wininger, speaking on the company's first quarter earnings call. "On the back-end, we built a first of its kind insurance operating system that lets our team service our customers efficiently and delightfully. This year, ChatGPT 4 and other large language models made a huge leap forward. The potential impact this technology brings to businesses like ours is substantial."

Since generative AI can reason and learn it has the potential to improve efficiency and customer service as well as risk assessment and underwriting decisions. "This technology will help us better anticipate customer needs, respond to more claims instantly and ultimately provide better coverage at lower costs," he said. "For our competitors, though, adapting to this change will not be easy. A traditional insurance company depends on hundreds of disparate software tools to run its business. many of which are outdated legacy systems built decades ago by third-party vendors."

Wininger's argument is that companies without an AI-friendly stack will be buried by technical debt. Lemonade's bet eight years ago revolved around conversational UI and chatbots and it has updated models as they have evolved. He said:

"Today, we use dozens of AI models to do pricing, underwriting, customer service, payments and many other internal operations. We even built our own internal AI framework to help us manage and deploy models seamlessly and quickly across the organization. In just a matter of days, our team was able to add ChatGPT and other generative AI tools to our platform. We now have more than hundred different initiatives, which we believe can have a meaningful impact on our business. As a result, we expect to see more savings in the next 18 months and anticipate continued improvements in both our expense and loss ratios."

Deutsche Telekom AG CEO Tim Hottges: Eying customer service benefits

Speaking on DT's earnings conference call, Hottges was inevitably asked about generative AI. He said:

"There was never in the last 20 years that I recall a technology that had so much impact on thinking in management but as well in the organization as the announcement of ChatGPT and OpenAI. This is really a game changer in the way we look at it."

DT launched a program that features a centralized team that works with OpenAI's ChatGPT as well as Large Language Models including fine tuning. "We are fine-tuning all the elements of it with our foundation in the customer service arena," he said. "We used it already in the past, but we will now trying to exponentially develop the area of chatbots, call center support, network optimization and other areas where big data is affected."

Generative AI guide: ChatGPT: Hype or the Future of Customer Experience

• What to Expect from Generative AI in Analytics and Business Intelligence
• Don’t Kill Innovation, But Apply Guardrails For AI
• How Generative AI Has Supercharged the Future of Work
• Coursera: Generative AI will lead to reskilling, upskilling boom

• Google I/O 2023: Google makes its generative AI case, Bard becomes ingredient brand

• At Google I/O 2023, Google Cloud launches Duet AI, Vertex AI enhancements

Liz Miller

Vice President & Principal Analyst Constellation Research

About Liz Miller: Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform…...

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When the Musk era of Twitter began, in a blog post I suggested that the first question the new owner would need to answer and articulate would be what Twitter actually was going to be moving forward:

Twitter is a media company: Twitter “must subsidize its capacity to host a broad, global, democratized media destination that holds professional accounts (from journalists and their publications to marketers and their brands) in equal footing to citizen creators… if this new massive recurring revenue base became predictable and stable over time, Musk could easily show advertising the door and instead charge a heftier fee to allow brands permission to even HAVE accounts.”

Twitter is an advertising company: Twitter “leverages citizen creators, brands and media accounts to attract more users hungry for quick snippets of information or engagement. This audience would, in turn, represent a massive potential audience for targeted promoted content and advertising…quantity of audience beats out quality and is a model where advertising pays the whole tab. “Cherry on top” revenue like subscriptions and priority access options like Twitter Blue become important for bigger numbers but are not the primary focus of revenue projections.”

For over six months, Elon Musk has done everything imaginable to turn Twitter into a media company. The results have not been great. The moves to prop up a subscription dominant business have not gone smoothly. According to a report in Bloomberg, the Twitter Blue subscription has only captured 1% of Twitter’s 500 million monthly users. According to Musk himself, advertising revenue had decreased by 50% between October 2022 and March 2023. There is little visible runway for Twitter to continue on this glidepath of being a subscription-centric media company.

The tweet-nouncement by Musk that NBCUniversal’s powerhouse sales leader, Linda Yaccarino, has joined Twitter as CEO feels like a clear sign that Twitter might be ready to shift course.

First, let’s dig into WHO Yaccarino is.

For all things I have personally heard about her, she is a powerhouse seller, dealmaker and business leader. She’s been credited with making some of the most lucrative deals in her tenure with NBCUniversal. Joining the company in 2011, Yaccarino was named the chair of global advertising and partnerships in October 2020 and her team has been credited with generating over $100 billion in advertising sales for one of the largest and more complex advertising portfolios of media properties that make up NBCUniversal.

When the rumor mill cranked into high gear in the late hours of May 11 most of the comments from advertising thought leaders was WILD approval noting that Yaccarino might be the ONLY executive out there to breathe life back into the ailing blue bird.

What does (or COULD) Yaccarino’s appointment really mean?

This could mean that Twitter will embrace being an advertising platform, bringing some stability to revenues and to the platform itself. This could also be an opportunity to bring back some of the content creators turned off by a once civil space for conversation turning into an almost daily shouting contest across differing ideologies.

But, as an advertising platform, this will mean that the significant and very real concerns advertisers have about content adjacency and moderation be addressed by serious people ready with serious answers. This will also give Twitter an exceptional opportunity to hit pause on hastily made subscription strategies that fostered more ill will with notable content creators than it did drive excitement over exclusive experiences.

As CEO, Yaccarino will need to dissect the business opportunities into segmented, distinct yet intersecting nuanced categories. If given the power, freedom, and capacity to do this, we could see new and even more profitable subscription types and experiences as Twitter evolves. She will need to reinvent the Twitter culture for both customers and employees and while this will initially be an exceedingly painful process (healing broken bonds where trust no longer exists is never easy and usually leaves scars somewhere) that doesn’t always work, it COULD result in something even better.

Musk, in his Tweet about the appointment, also pointed to his continued desire to turn Twitter into an “Everything” app – up until now, this has been an empty promise that felt more like being handed a burnt, stale everything bagel than an improved experience application. With Yaccarino’s arrival, there is the potential to bring that big dream into real world business focus. She could be the voice that articulates the opportunity for creators, consumers and advertisers…and all three parties have been missing this clear articulation of a Twitter vision since well before Musk’s takeover.

HOWEVER, this could also mean rough waters ahead if all Musk has done is hand over the title but withheld the territory from the CEO gig. In his own words, he will be staying on as “CTO in charge of the product.” But for many brands (and more than a few content creators) the product has been horrifically broken under his reign. If Yaccarino only has the mandate to bring advertisers back to a broken trough, it is unlikely we will see Twitter evolve beyond what it is today. And for the advertisers who DO return based on their relationships with Yaccarino and their trust in her skill and expertise, that return will only be as durable as her time is in the role.

Yaccarino is no slouch. She is smart, articulate, savvy and battle tested in some of the roughest media waters around. She isn’t going to wither in the face of irrational man baby tantrums. From what I have learned about her from those who call her a friend, she has a passion for the media business. My sincere hope for her…and frankly for all of us who have always wanted Twitter to succeed…is that she has been giving both title and territory. Only time will tell. And judging by how fast this strange timeline we are in has been moving, Yaccarino won’t have terribly long to make her mark and set the story of the new everything platform X also known as Twitter into motion.

(Image Credit: The image attached to this post was created using Adobe Firefly using the text prompt: Hyper Realistic Blue bird wearing armour standing in front of a burning fire)

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Wendy's move to deploy Google Cloud's generative AI technology for drive-thru ordering starting in June is worth watching as large language modeling (and the fine tuning for industry use cases) go mainstream.

Speaking on Wendy's first quarter earnings conference call, Wendy's CEO Todd Penegor said Wendy's Fresh AI pilot is part of a larger digitalization push.

"We have partnered with Google to pilot Wendy's Fresh AI, a voice AI solution for drive-through ordering that utilizes Google Cloud's generative AI and large language models technology. We believe this solution creates a huge opportunity for us to deliver a truly differentiated, faster and frictionless experience for our customers and allows our crew members to continue focusing on making great food and providing exceptional service.

 

We plan to launch this pilot in June and are incredibly excited about the potential unlocks to speed of service, customer satisfaction and profitability that this technology could drive over time."

Wendy's has been a Google Cloud partner and news of the Wendy's Fresh AI pilot was announced a day before Google I/O 2023. 

According to Wendy's, 75% to 80% of customers choose drive-thru as the preferred ordering channel. Wendy's is hoping that automation can make ordering more seamless. The catch is that the fast-food restaurant chain has to customize Google Cloud's models for menu options, terms unique to Wendy's and special requests.

The Wendy's FreshAI pilot launches in a Columbus, OH area restaurant and then will expand from there. Wendy's will use Google's Vertex AI and other models that were outlined yesterday.

• At Google I/O 2023, Google Cloud launches Duet AI, Vertex AI enhancements
• Google I/O 2023: Google makes its generative AI case, Bard becomes ingredient brand
• Google’s generative AI strategy from Google I/O 2023: Hits and misses
• AWS, Microsoft Azure, Google Cloud themes: Optimization, generative AI and the long game

This project is worth watching for a bevy of reasons. Here are a few takeaways and open questions to ponder:

Will this AI drive thru concept work this time? Constellation Research Analyst Liz Miller noted that the Wendy's pilot sounded a bit familar. That's because the AI in the drive thru experiment was tried a year ago. Here's Miller's history lesson:

In 2022, McDonalds launched an AI assistant in 24 locations after an initial 10 store rollout in 2021. By summer 2022, the company had only reached 80% drive thru voice ordering accuracy. The roll out stopped because McDonalds wanted 95% accuracy. McDonalds' AI assistant also was torched on TikTok. 

Panera, Sonic, White Castle, Checkers and Rally's also tried the AI drive thru technology. In 2022, the storyline was AI was being used to address talent gaps and labor shortages. Vendors include Open City, which has a Tori bot used at Popeyes, Presto, which counts Applebees and KFC as customers, and Valyant.

Wendy's and Google Cloud's models will have to hit their accuracy rates to expand from the pilot phase. 

What's the integration process with enterprise data? Wendy's is integrating Google foundational LLMs with data on the menu, business rules and logic, conversational guardrails and integration with restaurant systems including point of sale.

How are returns measured? Penegor said on Wendy's earnings call that efficiency and throughput will be primary metrics. Customer and employee satisfaction will also be core metrics. If FreshAI can speed up ordering, Wendy's can drive more sales velocity. Employees can focus less on the order station and more on food prep and expediting it.

What do companies need to do ahead of time to get to the generative AI phase? Hint: Get your data act together. Yes folks, master data management matters. Penegor said:

"I think now is the right time. We've done a lot of work on our tech stack and our restaurants. And we've had Kevin Vasconi, who joined us several years ago now from Domino's, and his team have done a nice job really setting ourselves up to lean in even more on technology. Clearly, it starts with the global next-gen design. That's all digital forward. We've got work that we can continue to do even on the digital menu board. So that's still growth in front of us."

Now Wendy's has been a Google Cloud partner since 2021, but its digital transformation efforts started with kiosks, mobile ordering and agile software development back in 2017. Through the first quarter, 12% of Wendy's sales were digital.

Wither the human drive-thru order taker? Should Wendy's FreshAI effort succeed, rest assured other restaurants will follow. Companies like Starbucks and McDonald's also have significant digital efforts as well as loyalty programs. Both companies have drive-thru operations as do a bevy of others in the category including Taco Bell, Chik-Fil-A and others. Also see: Starbucks’ new CEO: ‘We can enhance our tech stack to lower costs and reinvest’

Andy Thurai

Vice President and Principal Analyst Constellation Research

About Andy Thurai Andy Thurai is an accomplished IT executive, strategist, advisor, enterprise architect and evangelist with more than 25 years of experience in executive, technical, and architectural leadership positions at companies such as IBM, Intel, BMC, Nortel, and Oracle. Andy has written more than 100 articles on emerging technology topics for publications such as Forbes, The New Stack, AI World, VentureBeat, DevOps.com, GigaOm and Wired. Andy’s fields of interest and expertise include AIOps, ITOps, Observability, Artificial Intelligence, Machine Learning, Cloud, Edge, and other enterprise software. His strength is selling technology to the CxO audience with a value proposition rather than the usual technology sales pitch. Find more details and samples of Andy’s work on his…...

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Google I/O 2023 kicked off and the proceedings could be summed up in two words: Generative AI. Alphabet CEO Sundar Pichai and Google Cloud CEO Thomas Kurian walked through Google’s new models, how it’ll incorporate generative AI across the product line and advance business transformation.

Here’s a look at the hits and misses from Google’s strategy session on generative AI. Keep in mind, that this launch follows a rocky debut of Bard, which was upstaged by Microsoft’s ChatGPT rollout. In some areas, Google shined with its generative AI plans. In others, Google is playing catchup to the combination of Microsoft and OpenAI.

Hits

1. The Gmail feature of AI writing a contextual-based email is pretty good. You can have AI write emails based on context with short one-liner responses or detailed. The Help Me Write feature should boost productivity.

2. Google is known for its map capabilities and analysis of traffic patterns. Now with AI integration, someone can integrate traffic, weather, air quality, etc. when mapping out a route at different times and planning a trip ahead. The immersive view looks intriguing. When it comes to mapping Google owns it.

3. AI for image editing is very good. Available until now on Pixel phones only, it moves to Google Photos now. In addition to the Magic Eraser, the Magic Editor can allow for contextual editing easier without the need for expensive tools from Adobe. The additional integration with Adobe Firefly for graphic workers seems compelling.

4. The LLM model called Gemini when ready will be available in multiple sizes based on needs instead of boiling the ocean down like ChatGPT-4, etc.

5. I really like the option of identifying synthetic content with a combination of water marking and metadata embedding. This by far is the best responsible AI theme I have seen. As I repeated many times, fake content, especially during election cycles, can do much harm. This is a good start.

6. Generative AI integration with Google Workspace products such as Sheets, Docs, Gmail and Slides are all very good.

7. The AI-enabled "real-time" cognitive search to mix both Bard AI synthesized content along with regular Google search is brilliant. Combining those results with Google Shop can be good for websites and e-commerce enterprises. These features can be a differentiator for Google while Microsoft is struggling with the market size.

Misses

1. The variations of Codey, code generation tools offered by Google are still limited. CoPilot has been around for more than a year now and its code generation has been improving tremendously.

2. Microsoft has already started moving towards an industry-specific solution set using AI, but Google seems to be missing many steps in that direction.

3. While there were compelling releases, there was no mention of enterprise-specific integration with ERP, HR, CRM, and other systems. It is going to be hard for Google to gain traction without a broad integration strategy. Google did note a Salesforce integration.

4. While Kurian threw big numbers out there about AI-optimized infrastructure, AWS has the lead for enterprises that want to use variable sizing. Not sure if Google can catch up on that. The Google Cloud offering is extremely limited and didn't come across as compelling.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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PayPal, Block and Shopify have all reported earnings in recent days. Here's a look at what those three companies are saying about the economy, generative AI and their product plans.

PayPal: Controlling what it can

The economy

PayPal CEO Daniel Schulman said the company had a good start to the year but is also focusing on the things it can control given macroeconomic uncertainty. See first quarter results. 

Schulman said:

“Even with the strong start, there remain many challenging issues to navigate as we look forward. Both the macroeconomic and geopolitical environments are complex and difficult to predict.

In these times, the strong message I'm giving the PayPal team is to focus on the things we can control. We know that job number one is to invest and innovate to improve our value proposition to our merchants and consumers.”

Generative AI

PayPal is looking internally to leverage generative AI. Schulman said:

“With the new advances of generative AI, we will also be able to accelerate our productivity initiatives. We expect AI will enable us to meaningfully lower our costs for years to come. Furthermore, we believe that AI, combined with our unique scale and sets of data, will drive not only efficiencies, but will also drive a differentiated and unique set of value propositions for our merchants and consumers.

This is not just about efficiencies. By the way, it's not about cost reduction. It's about doing things better. There's no question that AI is going to impact almost every function inside of PayPal, whether it be our front office, back office, marketing, legal, engineering, you name it. AI will have an impact and allow us to not just lower cost but have higher performance and do things that are not about trade-offs. It's about doing both in there.”

The other thing that the teams are doing and doing extremely well is they're improving processes.

Venmo meet PayPal

Schulman added that PayPal and Venmo will be connected as part of product updates this year. He said:

“Later this year, we will add the ability for a Venmo user to pay a PayPal user and vice versa, bringing more utility to both customer bases. We are currently piloting the upcoming launch of Venmo teen accounts, which have been requested by both parents and teens for some time.”

Block: Macro challenges, Regulation, Global financial system shifts

The economy

Block Chairman and President Jack Dorsey laid out the landscape.

“There are three macro challenges affecting all businesses now and over the long-term. Number one, constant state of global crisis. Number two, regulatory fragmentation. Number three, global financial system shifts. The world seems to be moving from one global crisis to the next and suffering from an overwhelming amount of information, which is causing people and organizations of all sizes to be distracted and reactive to the moment. From COVID to inflation, to the war in Ukraine, to bank failures, the number of things we all need to pay attention to grows unbounded.”

Dorsey said the company has more than 30 products focused on specific verticals (see Block results). "We see a lot of growth upmarket because we provide flexibility," said Dorsey. "Our solutions addressing key verticals of restaurants, retail and beauty allow us to serve much more complex sellers with very specific needs, which again goes back to that flexibility point and the strength of our ecosystem. And the developer platform continues to be stronger and stronger as we move forward."

Regulation

Dorsey said:

“Regulators around the world are coming up with slightly or entirely different answers to problems facing their citizens. Instead of having global standards, we end up with rules which are different for every market, effectively slowing the pace of development. While this might be a good thing for each market and makes it very challenging to grow a global internet business, especially for smaller companies. Part of our job will be to help our customers navigate this complexity by taking it on ourselves.”

The future of money

Dorsey said:

“There have been numerous challenges to the global financial system, and it's experiencing some significant shifts, from new global reserve currency candidates, centralization of banks through failure of smaller ones, to adoption of central bank digital currencies with entirely new capabilities. These all affect our core business and are all trends we need to navigate carefully.”

Generative AI

Dorsey said that Block is focused on artificial intelligence and staying ahead of the curve. "More and more effort in the world will shift to creative endeavors as AI continues to automate mechanical tasks away and we believe we are well positioned for that shift with our strategy for artists on title," said Dorsey.

Shopify: Expanding into enterprise retail, shedding logistics

Shopify President Harley Finkelstein said the company is "leaning into our partner model ecosystem" with the sale of its logistics business to Flexport. The company also cut headcount.

"We also realized that in order to adapt and stay at the forefront of commerce, Shopify must operate with even greater speed and efficiency. So, we are making changes and refocusing the priorities that we believe will get Shopify to the size and the shape necessary to unlock the next era of growth and innovation," he said.

Shopify expanded its merchant base across all geographies and merchant sizes.

Targeting large retailers

The company said it had success selling its enterprise retail product, Commerce Components by Shopify (CCS). CCS is a composable stack where retailers can use Shopify components they want and integrate them with existing systems. The move makes Shopify checkout and storefronts available to large retailers.

"There is a perception shift happening in the marketplace as enterprises begin to realize that they are now able to combine Shopify's cutting-edge commerce solutions with their existing infrastructure, all while optimizing their operating expenses," said Finkelstein. Shopify has added large retailers such as Tim Hortons, Ted Baker and Zulily, which is owned by QVC.

In addition, Shopify inked partnerships with IBM Consulting and Cognizant to expand its reach.

Shopify is also thinking globally as 15% of its total GMV was cross-border. Market Pro has been scaling as Shopify handles international commerce headaches such as taxes on the back end for businesses.

For its core business, Shopify is driving usage of the Shop App and Point-of-Sale offerings.

Generative AI

Finkelstein said Shopify has "one of the best chances of using AI to help our customers."

He said:

"How do we integrate it into the tools that help us build and ship better products to our merchants. You're already seeing that in certain areas of Shopify. For example, the task of writing product descriptions is now made meaningfully easier by injecting AI into that process. And what does that -- the end result of that is merchants spend less time running product descriptions and more time making beautiful products and communicating and engaging with their customers."

Shop at AI is also an effort to create "the coolest shopping concierge on the planet, whereby you as a consumer can use Shop at AI and you can browse through hundreds of millions of products," said Finkelstein.

More importantly, Shopify is looking to AI to drive experiences and the products delivered to merchants.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Google I/O in previous years focused on Android, Pixel devices and cool features such as Magic Eraser. This year, Google I/O is all about the models.

Against the backdrop of a never ending stream of generative AI announcements and Microsoft's move to infuse its applications with OpenAI's ChatGPT, Alphabet CEO Sundar Pichai took the stage and made the case for its generative AI advances. "AI is having a very busy year," quipped Pichai. Here's the case in a nutshell.

Google has been using AI for years. Pichai said Google has been using AI to be more helpful for years with features such as smart reply in Gmail, Magic Eraser in Google Photos and various Maps innovation. "Today, we are taking the next generative AI step with a bold and responsible approach across all of our products," said Pichai.

AWS, Microsoft Azure, Google Cloud themes: Optimization, generative AI and the long game

Google is innovating with its models. The company launched PaLM 2, which has various models aimed at mobile as well as larger implementations. "25 products and features are delivered by PaLM 2 today," said Pichai.

The demos highlighted how a coder could fix a bug and add comments in Korean.

PaLM 2 was also highlighted in a medical analysis of an Xray to highlight specific use cases.

Bard is an ingredient brand. Bard has been updated and will have extensions to various applications. Built on PaLM 2, Bard will be updated to handle images and update them. A demonstration featured a natural language question about universities in Pennsylvania, refining the results through questions and putting the answer in a Google Sheet.

Bard is also out of waitlist mode and will be available in 180 countries.

Google Workspace will use generative AI to boost productivity. Generative AI capabilities are being added to Gmail, Docs, Sheets, Slides and Meet. Demos included using generative AI for job descriptions, marketing content and emails using the Help Me Write feature. The idea is that generative AI supplies the starter content for refinement. In Sheets, generative AI can create starter tables.

Search gets conversational. Google search will also use generative AI where Google will add aspects to consider when making a purchase as well as reviews from Google Shopping Graph. Google will be rolling out new experiences in search including "converse" or "as a follow up question." There will also be a conversational mode for search that aims to understand your intent. Experiences will be integrated so more results can be found with a scroll. 

Constellation Research analyst Holger Mueller said: "Google elevates the search battle by making search multimodal - AI adjacent to traditional search results... and even in dialogue mode - traditional search results will show up. That's a good compromise for traditional usage - and a more fail safe approach to introducing AI into search than the current solely conversational UX approaches." 

Android 14 will get generative AI features. Messages will get Magic Compose, which will use generative AI to adjust tone such as more professional or playful. There will be new customizations for wallpapers will use generative AI for cinematic photos as well as original wallpapers.  Pixel devices will also leverage generative AI for Pixel Call Assist, Pixel Speech and new camera features. 

More models are coming. Google outlined Gemini, a new model in development. Gemini will be able to find synthetically generated content via watermarking and metadata.