Generative AI's looming crap in, crap out data problem

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Generative AI models are going to have a big training data issue as public web access becomes more restricted and it's unclear whether large language models (LLMs) will be able to avoid the garbage in, garbage out issue.

This data access issue is just getting started, but there's enough developing to see the wall ahead. Constellation Research CEO Ray Wang has said that the open web will largely disappear as content providers and corporations restrict data access. If this scenario plays out, LLMs aren't going to have the training data available to continually improve.

“We will not have enough data to achieve a level of precision end users trust because we are about to enter the dark ages of the internet, where the publicly available information on the internet will be a series of Taylor Swift content, credit card offers, and Nvidia and Apple SEO. Where will the data come from?” said Wang.

• 14 takeaways from genAI initiatives midway through 2024
• Meet Data Inc. and what a post AI company looks like
• GenAI, originality and scaling lookalikes

Here are a few developments that have me wondering about the data wall we're going to hit.

Cloudflare last week announced a new feature for its customers that would prevent AI bots from scraping data from sites. There has long been a robots.txt standards that prevents information from being indexed by search engines. The general idea was that the robots.txt approach would also give creators the ability to prevent content from being used for LLM training data.

The reality is that the AI bots are blowing right past that robots.txt approach. Cloudflare's post on disabling AI bots is worth a read. A few highlights include:

Bytespider, Amazonbot, ClaudeBot, and GPTBot are the top four AI crawlers. Bytespider is run by Bytedance, the parent of TikTok. "We hear clearly that customers don’t want AI bots visiting their websites, and especially those that do so dishonestly. To help, we’ve added a brand new one-click to block all AI bots," said Cloudflare.

If you play this out, you can rest assured that the most credible sites are going to block AI bots. After all, why give the content away that you can license? Google licensed Reddit content. Media giants are pairing up with Google or OpenAI.

Reddit laid out the open internet meets AI conundrum in May:

"We see more and more commercial entities using unauthorized access or misusing authorized access to collect public data in bulk, including Reddit public content. Worse, these entities perceive they have no limitation on their usage of that data, and they do so with no regard for user rights or privacy, ignoring reasonable legal, safety, and user removal requests. While we will continue our efforts to block known bad actors, we need to do more to restrict access to Reddit public content at scale to trusted actors who have agreed to abide by our policies."

This potential data wall for genAI is so critical that synthetic data is becoming increasingly important. The general idea behind synthetic data is that models will generate content that will then be used to train future models.

Last month, Nvidia released Nemotron-4 340B, a family of models optimized for Nvidia NeMo and TensorRT-LLM, to advance synthetic data. Nvidia CEO Jensen Huang has a vision that includes AI factories creating data and then learning from it to create more models.

That Nvidia synthetic data vision only works if there's a continuous stream of quality data to ingest. Companies like Google and Meta have those streams since users create data every second. Most LLM players won't have that access and will aim to avoid licensing.

Add it up and we may see a reverse data flywheel. More creators pull data and content from the open web. LLMs train on what's available. You get what you pay for, so the data is crap. Then these models trained on crap data train more models. If this data quality issue doesn't get sorted out, the only thing generative AI is going to scale is crappy models.

GenAI, orginality and scaling lookalikes

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Generative AI appears to be scaling lookalikes at a rapid clip and the big unknown is how long originality will last. 

Figma's Make Designs feature is the latest example of how generative AI models and the guardrails that govern them are going to have weight how much they can crib from existing designs. When does "inspiration" become a blatant copy of something?

As a quick recap, Figma launched Make Designs, a feature that can create apps on the fly. Andy Allen, CEO of Not Boring Software, highlighted on X how Figma's Make Designs tool replicas of Apple's weather app. I'd argue that the Figma Make Designs creations looked like the weather apps you'd find everywhere. Honestly, most Web designs and apps all look alike today. GenAI is just going to scale copycats even more.

Figma CEO Dylan Field responded to Allen's take in a thread that noted that the company used off-the-shelf models, notably OpenAI, and that the issue was variability. Figma didn't have enough data to create more original designs.

Field wrote:

"How does Make Design work? As we have explained publicly, the feature uses off-the-shelf LLMs, combined with design systems we commissioned to be used by these models. The problem with this approach — which I outlined in my keynote last week — is that variability is too low."

The upshot to Field's response is that generative AI can scale creativity, but it needs a large data set. However, if all the data in the training set takes inspiration from the same thing you're going to have a lot of lookalikes.

The one certainty is that the Figma kerfuffle is just the beginning. We're going to hear about these issues repeatedly until the overarching genAI systems are designed better.

For context on the issue, I asked the Constellation Research team to provide some thoughts. Every enterprise is going to use off-the-shelf models so you should know the landmines in advance. Here's what Liz Miller had to say:

"At Config, while the release of Make Design got some oohs and ahhhs…it didn’t get the room thundering cheers. That honor went to the release of Slides of all things! Figma users were most excited by automation and collaboration tools that actually help them get their jobs done and done better. So, while the generative AI tools were “cool” they weren’t dominating conversations. That went to updates and new features in tools like Dev Mode that brings developers and designer workflows and work closer together.

This “story” is going to happen more and more as GenAI tools come out of beta. The key question asked by Figma’s CEO is a critical one: what was this foundation model trained on? That’s an OpenAI question. Was the issue the design framework they had commissioned or was OpenAI trained on Apple design frameworks as their model for “best” design?

Sadly, this is often where and how UX and product design goes…even when AI isn’t involved. Remember the days when bootstrap design templates dominated design. Everything looked like it was a knockoff of the Uber website! Tastes tend to follow the leader until everything looks alike. It is a lot like everyone running out and painting their house white with black accents. It looks great on those first homes, but next thing you know, EVERY HOUSE on the block is white with black trim. That is until someone paints their house black with wood trim and the design aesthetic takeover begins again, This time, thanks to Generative AI, the takeover happens at lightning pace and scale. If there was ever a time to make sure a human was in the loop it is for design…and in reality…that’s exactly what Figma did."

Holger Mueller added:

"The Figma issue shows the dilemma of all generative AI--it needs data. For an app developer or UX developer an app needs to look at existing artefacts of work. And ideally how popular they are. The demand to create a weather app suggests a design that looks like the Apple weather app is no surprise. It is a bona fide weather app, has recently been designed and is used by millions of users across form factors every day. Those are all good qualities to 'steal' for some design features. But the grounding of the model means it cannot take 100% of an existing app. It can only take input or inspiration from an existing app up to 10%. That model design seems to have been missing. Kudos to Figma for not giving up and retooling."

More on genAI dynamics:

• 14 takeaways from genAI initiatives midway through 2024
• OpenAI and Microsoft: Symbiotic or future frenemies?
• AI infrastructure is the new innovation hotbed with smartphone-like release cadence
• Don't forget the non-technical, human costs to generative AI projects
• GenAI boom eludes enterprise software...for now
• The real reason Windows AI PCs will be interesting
• Copilot, genAI agent implementations are about to get complicated
• Generative AI spending will move beyond the IT budget
• Enterprises Must Now Cultivate a Capable and Diverse AI Model Garden
• Financial services firms see genAI use cases leading to efficiency boom

Persistent Systems acquires Starfish Associates

Persistent Systems said it will acquire Starfish Associates that expands its reach into the contact center and unified communications market.

Terms of the deal weren't disclosed.

With Starfish Associates, Persistent Systems gets a large enterprise customer base and its automation, integration and workflow engine. Starfish Associates integrates communication systems from the likes of Amazon Connect, Avaya, Cisco, Genesys and Microsoft Teams with platforms from ServiceNow, Workday and Microsoft.

Persistent Systems said its plan is to combine Starfish Associates with its AI-automation tools to optimize workflows.

Here's a look at the Starfish Associates platform.

Sandeep Kalra, CEO of Persistent Systems, said Starfish Associates "greatly enhances our unified communications and contact center management offerings as this industry undergoes significant disruption on the back of AI-led innovations." Persistent Systems' services footprint includes consulting, cloud and infrastructure, data and analytics, software product engineering, automation, application development, CX transformation, security and enterprise integration.

Persistent Systems recently launched its GenAI Hub, a platform for creating and deploying generative AI applications in an enterprise based on multiple large language models. Persistent also launched iAURA, a suite of data tools for AI and machine learning implementations.

The company also announced partnerships with Google Cloud, Snowflake and AWS to expand genAI use.

For fiscal 2024, Persistent Systems delivered revenue of $1.186 billion, up 14.5% from a year ago. Persistent was named Constellation Research's Best Enterprise Services Vendor in 2023 and appeared on multiple Shortlists.

• Constellation ShortList™ Innovation Services and Engineering
• Constellation ShortList™ Public Cloud Transformation Services: Global
• Constellation ShortList™ Custom Software Development Services

Tableau CEO Aytay on genAI, the future of analytics, precision decisions

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Tableau President and CEO Ryan Aytay said the company's future as part of the Salesforce product portfolio is to leverage generative AI in the future to offer "precision decisions" and a semantic layer that can democratize analytics and enable data sharing.

Aytay's appearance on DisrupTV was a month after Tableau's user conference. The company announced extensibility and usability feature and free local file sharing in Tableau Desktop Public. Tableau also announced Einstein Copilot for Tableau in beta, Tableau Pulse, which connects KPIs and insights, and Tableau+, a package for customers that want to provide access across an enterprise.

Tableau also launched more than a dozen new features that were showcased at the conference.

Tableau and Salesforce Eye Next Wave of Analytics and BI | Analytics and Business Intelligence Trends in Cloud, Embedding, and Generative AI

Before becoming CEO at Tableau, Aytay was the company's Chief Revenue Officer (CRO) for more than a year. Prior to Tableau he was Salesforce's Chief Business Officer. Here are some of the key takeaways from Aytay's DisrupTV chat.

The transition to Tableau CEO. Aytay's position as Tableau's revenue chief gave him a lot of opportunities to "learn the business and learn our customers." Aytay said the CRO role requires you to listen to customers and partners and see what's working and not and how to improve the experience.

"One of the key things for any role you start is that you have to be aware of what's happening and not just assume you know the answer because often you only know your own perspective," said Aytay.

Working with Tableau's community. One of the more unique things about Tableau is that it has a strong community of more than 4 million members. That tally has doubled since Salesforce acquired Tableau in 2019. "The community is a really big part of the business and an opportunity for customers and partners to learn from each other," said Aytay. "The community helped to bring training materials to learn and transition into the world of self-service analytics. Now we're into this core personalization and consumerization which is all about AI. The community is helping people move in that direction. It's a support system and ecosystem. My job is to really listen to them."

Aytay said he met with 30 customers in June to talk shop and everyone has been experimenting and trying to figure out the role of the digital worker. "I think we're still in the mode of the human interacting with a kind of digital worker," he explained. "In the longer term, the digital worker will become better and there will be a partnership with the technology."

Constellation Research analyst Doug Henschen said in a recent research note:

"Given that some 70% percent of Tableau customers do not use other Salesforce products, Tableau execs struck all the right chords to reestablish the importance of the brand and the DataFam, and to reinforce Tableau’s differentiation as a best-of-bread analytics and BI market leader. At the same time, they also acknowledged that Salesforce, with its deep pockets, its huge ecosystem, and its bevy of existing tech assets, will be indispensable and inseparable in helping Tableau to evolve."

Community and product development. Aytay said Tableau's product development is heavily influenced by the community because it "is the most in tune with what's happening."

"What's happening and what product requirements do we need to be thinking about. The community is like this heartbeat, and we need to do a lot for them, and they do a lot for us. It's a partnership. The best products have a strong community.

One of the best parts of my job is that I get to talk to the community members. I can tell you that we get a lot of feedback and that we need to change things. We're already talking to them about what's coming to give us feedback. They give us a bunch of feedback, and we try to make adjustments to things we don't always get right. You just have to be authentic and walk into these situations and talk about listening. Once you receive information you have to act on it."

Generative AI and safety. Aytay said generative AI has gone a long way to consumerizing AI, but it's still uncertain how it applies to the enterprise. "What's great about generative AI is that it has a lot of momentum. In a business or enterprise, you need to make sure you have a big data strategy to make sure you're not sending your company information into the open Internet," he said. "That's the journey and we can go with our community to teach businesses, organizations and nonprofits to be careful. I think we're in a learning environment right now."

GenAI and Tableau. Aytay said:

"First of all, we have to deliver what customers need right now. We've delivered products to the market that are useful. We have Einstein Copilot for Tableau, and it has been rapidly adopted.

But as we look to the next wave, the future of Tableau is really about going beyond seeing and understanding your data and that standard intelligence experience."

Aytay said companies have multiple data silos and your data has to support multiple people and roles. What's needed is a semantic layer that will bring all the data together a unifying it. That's a key part of Tableau's new products.

Marketplaces and sharing will also be a big part of the product roadmap. Aytay said:

"If there's a great visualization, data, data prep, data calculation or semantic model I should be able to share it in my four walls of the business and externally. That sharing is a radical change that is being built natively with AI."

Precision decisions. Aytay said that enterprises should be able to ask questions of the business in the flow of work in real time. The vision of analytics has been about actually making decisions in business.

"It's not just about looking at dashboards," said Aytay. "How do I make the best decision possible leveraging all the data in my business?"

Education tech in turmoil amid genAI: Why consolidation is next

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

The education technology market has been rattled by generative AI, cautious enterprise and institutional spending and a set of overlapping companies with similar annual revenue profiles.

What's next? A merger and acquisition wave that's just getting started. The jockeying for position is already underway, but private equity will roll these companies together or they’ll merge on their own.

• In March, Accenture said it will acquire Udacity and absorb its employees to create Accenture LearnVantage. Accenture's plan is to use LearnVantage to reskill and upskill people in technology, data and AI.
• In May, Bain Capital said it will acquire PowerSchool for $5.6 billion. Meanwhile, Coursera and Chegg have been crushed by investors and now may look like buyout targets.
• Instructure Holdings, the company behind Canvas, is reportedly in play to go private again. Thoma Bravo, which already owns 83% of Instructure, acquired the company for about $2 billion in 2020 and then took it public a year later at $20 a share. Now Reuters reports that Thoma Bravo is gauging private equity interest in Instructure. Instructure's market cap today is north of $3 billion.

Here's a look at the education technology players and what they're planning for the reskilling boom that has yet to arrive.

This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

Coursera: Reskilling in genAI era tricky

Coursera has three operating units--consumer, enterprise and degrees. Consumer revenue was up 18% in the first quarter compared to a year ago and enterprise and degrees revenue was up 10%. AI courses were driving demand in consumer and building in enterprise and degrees.

What's the problem? Coursera's first quarter results were mixed and the second quarter outlook disappointed.

Simply put, Coursera has been in the penalty box since April. Coursera CEO Jeff Maggioncalda said, "we remain in the early stages of understanding how generative AI will reshape the way we live, learn and work."

Nevertheless, Coursera's plans and platform look solid. The company did see softness in North American subscribers, but has plays in higher-ed as well as corporate reskilling. The company is also using genAI to bolster its content.

Coursera has more than $725 million in cash and short-term equivalents and a market cap of $1 billion.

Chegg in turmoil

Chegg showed strong growth during the Covid-19 pandemic and has since struggled with declining subscriptions and fears that generative AI will hamper future business.

The company has swapped CEOs and cut headcount by 23%, or about 441 employees. In April, Chegg said second quarter revenue will be between $159 million to $161 million, a range that was well below Wall Street estimates.

In a shareholder letter that went along with its restructuring, new CEO Nathan Schultz said the company is going all-in on generative AI to offer better learning experiences. Schultz added that Chegg will provide 360-degree individualized support for students that will couple proactive guidance and a combination of AI, content and human experts.

Schultz said the plan is to become more efficient, consolidate platforms and expand internationally. Chegg will also ink commercial agreements with educational institutions. Typically, Chegg has marketed directly to students. "We plan to roll out an expanding marketing and branding program, build more AI-driven functionality and tools, localize our services internationally and layer in new non-academic offerings that address the whole student," said Schultz.

For now, Chegg needs to return to subscriber growth and remains in the penalty box. Chegg could also look enticing to private equity due to its brand with students and reality that transformations are best done without the quarterly results grind.

Instructure's powerful position with Canvas

It's unclear where Instructure shares would be without the report that Thoma Bravo is shopping the company. It's quite possible that Instructure would fall along with the rest of the education technology space.

Nevertheless, Instructure's position with Canvas--the education operating system is valuable. In its first quarter, Instructure reported revenue of $155.5 million, up 20.7% from a year ago. The company reported a net loss of $21.1 million.

The company guided to second quarter revenue of $166.5 million to $167.5 million with non-GAAP operating income of $66 million to $67 million. For the fiscal year, Instructure is projecting revenue of $656.5 million to $666.5 million with non-GAAP net income of $123 million to $127 million.

Here's the rub: Instructure has total debt of $1.17 billion as of March 31.

CEO Steve Daly said Instructure will continue to innovate with the Canvas Learning Management System (LMS) and be a cog in education digital transformation projects. Daly added that the education market is uncertain, but demand interest remains strong.

Daly said:

"The consolidation and optimization of technology resources continues to be a high priority, and the LMS is the natural place for consolidations to happen. Customers are pulling us into more broad-based digital transformation discussions and see Instructure as a platform for consolidating their tech stack. This is a long-term trend, and we believe our expanding portfolio of products, especially our EdTech effectiveness solutions, as well as the extensive reach of our partner ecosystem position us as the partner of choice for consolidation."

Instructure could be a consolidator in the education technology market. In February, Instructure completed the purchase of Parchment, which operates an academic credential market platform.

PowerSchool going private

PowerSchool is being acquired for $5.6 billion, or $22.80 per share, by Bain Capital. PowerSchool, which makes software for the K-12 education market, supports more than 55 million students and 17,000 customers.

The company announced the general availability of PowerSchool PowerBuddy, a generative AI assistant for teachers and students that personalizes learning plans to improve student engagement.

PowerSchool went public at $18 a share in 2021 and was trading in the $16 range before the Bain purchase.

In the first quarter PowerSchool reported revenue of $185 million, up 16% from a year ago. The first quarter net loss was $22.8 million. Annual recurring revenue (ARR) was $720.3 million.

Udemy: Rides AI training wave

Udemy reported first quarter revenue of $196.8 million, up 12% from a year ago, with a net loss of $18.3 million. Non-GAAP net income was $5.3 million.

The company is focused on online skill development and has more than 16,000 enterprise customers.

Udemy looks more like Coursera in that it has consumer and enterprise businesses. The company projected second-quarter revenue of $192 million to $195 million and annual revenue of $795 million to $805 million.

Gregory Brown, CEO of Udemy, said on the company's first quarter earnings call said:

"Udemy is differentiated by the high quality, immersive and localized learning experiences we provide. Our comprehensive solution is purpose-built to provide three essential learning modalities, on-demand, immersive and cohort based. This combination allows us to offer an end-to-end solution where professional learners and organizations around the world can easily identify and quickly develop the skills, they need to deliver better business outcomes today and in the future." 

In addition, Udemy has been riding the AI training and IT certification wave. "In just over a year since Chat GPT launched, we’ve seen more than 4 million enrollments in the 2,000 plus AI courses in the Udemy catalog," said Brown. "This massive surge in interest from individuals and organizations demonstrates the rapidly growing need to upskill talent on generative AI. Based on what we’ve seen in the past year, we believe generative AI will have a significant lasting impact across nearly every industry, region and professional role."

Data centers in space: Feasible, sustainable and could drive returns

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Data centers in space are economically feasible and could reduce carbon emissions as workloads for generative AI surge, according to Thales Alenia Space, the coordinator of a European Commission study.

In a statement, Thales Alenia Space, a joint venture between Thales and Leonardo, said that space-launched data centers could drive returns of several billion euros between now and 2050 while moving the EU to net-zero carbon in the same time frame.

The study included expertise from environmental experts (Carbone 4, VITO), cloud computing (Orange Business, CloudFerro and HPE), launchers (ArianeGroup) and orbital systems (Germany's space agency, Airbus and Thales Alenia Space).

Space-based data centers are a topic that's folded under the European Commission's Horizon Europe program. This space cloud for Europe concept falls under a program called ASCEND (Advanced Space Cloud for European Net zero emission and Data sovereignty).

Key points in the feasibility study include:

• Developing and operating data centers in space would significantly reduce CO2 emissions.
• Data centers in space would not require water cooling and could run on solar power.
• The big issue is that a launcher would need to be developed that is 10 times less emissive over its life cycle.
• Returns on investment would justify building a high-capacity, environmentally friendly reusable launcher.
• Modular space infrastructure would be assembled in orbit using robotics from the EC's EROSS IOD (European Robotic Orbital Support Services In Orbit Demonstrator) led by Thales Alenia Space, scheduled to fly its first mission in 2026.
• The ASCEND project would also support Europe's digital sovereignty.

The partners in ASCEND now plan to flesh out the feasibility study and optimize the results with the aim of building out a roadmap for deployment in 2030.

Will we see data centers in space soon? It's unclear. The feasibility study noted that development plans would require European supply chain support, space access, orbital servicers, in-orbit assembly and manufacturing. However, it's possible that private sector entities could pursue similar plans.

Bottom line: Space data centers could cover a bevy of bases--data sovereignty, sustainability and capacity--issues and are worth pursuing.

Ian Cole’s CX Mission at Give Kids The World Village: 'Do Amazing Things'

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

For Ian Cole, chief innovation officer of Give Kids The World Village (GKWV), returns on technology investments are measured in smiles.

GKWV is an 89-acre nonprofit “storybook” resort in Kissimmee, Florida, that gives children with critical illnesses and their families from around the world week-long cost-free vacations.

The goal of GKWV is straightforward and laudable: give families that may have never had a vacation due to challenges an experience that will last a lifetime. Since 1986 GKWV has served more than 200,000 families from all 50 U.S. states and 77 countries, enabling them to laugh, play, and create unforgettable memories away from hospital stays and medical treatments.

“Customer experience is important no matter what you’re doing, but I think it’s especially important if you’re in the nonprofit world and you’re trying to do good for groups of people in despair,” says Cole. “You’ve got to make sure that every one of the people involved has a great experience, whether it’s a volunteer or a donor or the end beneficiary of what you’re doing.”

Cole, who leads the IT team that oversees networks, applications, security, mobile and desktop devices, and interactive experiences, worked with Avaya Customer Experiences Services (ACES) to give technologies to the onsite guest support team for creating guest experiences. His efforts at GKWV made him a CX for Good winner in Avaya’s CX Force Awards.

For Cole, technology projects aim to address current challenges and set up the future. He recently used Avaya to move from analog lines to Session Initiation Protocol (SIP) to boost reliability while cutting costs, implement a system for 911 emergency responders, and upgrade cloud and artificial intelligence (AI) features. GKWV uses Avaya unified-communications-as-a-service (UCaaS) and Avaya contact center solutions.

Related: How Virginie Nowak blended employee and customer experiences at Access Bank

GKWV has unique communications needs, because it is located in Florida’s Lightning Alley and needs to ensure uptime. The communications systems also need to ensure that responders have the necessary information about their clients, who may have unique health issues.

Here’s a look at some of the technology projects planned with ACES to enable the guest services team to personalize visits:

• Machine translation to give guests an experience in their native language. GKWV’s services support teams speak primarily English and Spanish.
• A digital scavenger-hunt bot for guests on the day of arrival. The bot enables parents to explore the village while children engage in an activity. Clues are readable on any smartphone and can be played back with text-to-speech.
• A concierge bot for navigation and guest information in multiple languages.
• A bot that enables volunteers to rapidly get answers and sign up for available slots.

These projects have to run on a tight budget, so GKWV does the best it can with the dollars entrusted to it by donors. “As a nonprofit organization, it’s very important for us to make sure that we pick the tools, technologies, and processes that we can support, both financially and technologically,” says Cole. “It would be very easy to chase the latest and greatest thing, but we’ve got to make sure that we’ve got the partnerships, relationships, and internal team to support those things. If we get that right, we can do amazing things.”

As for returns, Cole’s contributions to GKWV are measured in smiles. Each wish child can personalize a gold star for Stellar the Star Fairy to place on the ceiling of the Castle of Miracles and the Star Tower. The facilities—including pools and rides—are accessible to all children. And GTKW is planning to launch Mayor Clayton’s WonderLab STEAM Education Center this year.

Other 2024 CX Force Winners include:

• CX for Education. Tara Pasalic, systems integration specialist, McMaster University. Pasalic is an early adopter of cloud contact center as a service and a longtime Avaya customer. McMaster University focused on improving experiences for international students leveraging Short Message Service (SMS) messaging and call center resources.
• CX for Employees. Jayne Hogle, director of Unified Communications, American Heart Association. According to Hogle, customer experience at the American Heart Association is really about being heard. The technology plan has focused on everything from automated responses to call-to-ticket workflows and self-service tools made possible with a migration to the cloud. 
• CX for Healthcare. Rafael Sousa, chief technology officer, Hospital Nipo-Brasileiro (HNIPO). Sousa led an effort to link customer experience, hospital operations, and patient outcomes. Leveraging Avaya, Sousa has been able to provide faster and more personalized assistance to patients and route them to appropriate departments.
• CX for Growth. Hugh Carr, director of Customer Services, Standard Focus. Carr has been able to leverage Avaya customer experience technologies to improve experiences and boost revenue growth. By focusing on customer journeys, Standard Focus is reducing costs per contact by leveraging bots for easy issues and using humans for complex situations. The result is customer trust and more revenue.
• Rising CX Superstar. Emily Stubbs, director of Customer Experience, Aerflo. Stubbs has focused on funneling customer experience data into business intelligence tools to build views that head off customer issues before they happen. The proactive approach is critical to product launches and the customer experiences associated with them.
• CX for Transformation. Virginie Nowak, group chief customer experience officer, Access Bank PLC. Nowak implemented a broad customer experience transformation that has delivered returns across a bevy of metrics. Now Nowak is looking to future-proof customer experience so the bank can double the number of people it serves.