In March, several YouTube content creators seemed to receive a private video from the platform’s CEO, Neal Mohan. It turns out that it was not Mohan in the video, rather an AI-generated version of him created by scammers out to steal credentials and install malware. This may stir memories of other recent, high-profile AI-powered scams. Last year, robocalls featuring the voice of President Joe Biden urged people not to vote in the primaries. The calls made use of AI to mimic Biden’s voice, AP News reports. Examples of these kinds of deepfakes — video and audio — are popping up in the news frequently. The nonprofit Consumer Reports reviewed six voice cloning apps and reports that four of those apps have no significant guardrails preventing users from cloning someone’s voice without their consent. Executives are often the public faces and voices of their companies; audio and video of CEOs, CIOs, and other C-suite members are readily available online. How concerned should CIOs and other enterprise tech leaders be about voice cloning and other deepfakes? A Lack of Guardrails ElevenLabs, Lovo, PlayHT, and Speechify — four of the apps Consumer Reviews evaluated — ask users to check a box confirming that they have the legal right to go ahead with their voice cloning capabilities. Descript and Resemble AI take consent a step further by asking users to read and record a consent statement, according to Consumer Reports. Related:Why Your Business Needs an AI Innovation Unit Barriers to prevent misuse of these apps are quite low. Even for the apps that require users to read a statement could potentially be manipulated by audio created by a non-consensual voice clone on another platform, the Consumer Reports review notes. Not only can users employ many readily available apps to clone someone’s voice without their consent, they don’t need technical skills to do so. “No CS background, no master’s degree, no need to program, literally go on to your app store on your phone or to Google and type in voice clone or deepfake face generator, and there’s thousands of tools for fraudsters … to cause harm,” says Ben Colman, co-founder and CEO of deepfake detection company Reality Defender. Colman also notes that compute costs have dramatically dropped within the past few months. “A year ago you needed cloud compute. Now, you can do it on a commodity laptop or phone,” he adds. The issue of AI regulation is still very much up in the air. Could there be more guardrails for these kinds of apps in the future? Colman is confident that there will be. He gave testimony before the Senate Judiciary Subcommittee on Privacy, Technology, and the Law on the dangers of election deepfakes. Related:What’s New in Augmented Reality and Virtual Reality? “The challenges and risks created by generative AI are a truly bipartisan concern,” Colman tells InformationWeek. “We’re very optimistic about near-term guardrails.” The Risks of Voice Cloning While more guardrails may be forthcoming, whether via regulation or another impetus, enterprise leaders have to contend with the risks of voice cloning and other deepfakes today. “The burden to entry is so low right now that AI voices could essentially bypass outdated authentication systems, and that’s going to leave you with multiple risks whether there’s data breaches, reputational concerns, financial fraud,” says Justice Erolin, CTO of BairesDev, a software outsourcing company. “And because there’s no industry safeguards, it leaves most companies at risk.” Safeguarding Against Fraud The obvious frontline defense to defend against voice cloning would be to limit sharing personal data, like your voice print. The harder it is to find audio featuring your voice, the harder it is to clone it. “They should not share either personal data or voice or face, but it’s challenging for CEOs. For example, I’m on YouTube. I’m on the news. It’s just a cost of doing business,” says Colman. Related:Building Trust with Conversational AI: How to Avoid Common Pitfalls CIOs must operate in the realities of digital world, knowing that enterprises’ leaders are going to have publicly available audio that scammers can attempt to voice clone and use for nefarious ends. “AI voice cloning is not a futuristic risk. It’s a risk that’s here today. I would treat it like any other cyber threat: with robust authentication,” says Erolin.Given the risks of voice cloning, audio alone for authentication is risky. Adopting multifactor authentication can mitigate that risk. Enabling passwords, pins, or biometrics along with audio can help ensure you are speaking to the person you think you are, not someone who has cloned their voice or likeness. The Outlook for Detection Detection is an essential tool in the fight against voice cloning. Colman likens the development of deepfake detection tools to the development of antivirus scanning, which is done locally, in real time on devices. “I’d say deepfake detection [has] the exact same growth story,” Colman explains. “Last year, it was pick files you want to scan, and this year, it’s pick a certain location, scan everything. And we’re expecting within the next year, we will move completely on-device.” Detection tools could be integrated onto devices, like phones and computers, and into video conferencing platforms to detect when audio and video have been generated or manipulated by AI. Reality Defender is working on pilots of its tool with banks, for example, initially integrating with call centers and interactive voice response (IVR) technology. “I think we’re going to look back on this period in a few years, just like antivirus, and say, ‘Can you imagine … a world where we didn’t check for generative AI?’” says Colman. Like any other cybersecurity concern, there will be a tug of war between escalating deepfake capabilities in the hands of threat actors and detection capabilities in the hands of defenders. CIOs and other security leaders will be challenged to implement safeguards and evaluate those capabilities against those of fraudsters. source

With the right strategy and the appropriate services, you can reduce the risks of compliance violations…and increase efficiency at the same time. source

By Crystal Owens ( March 25, 2025, 6:25 PM EDT) — New Mexico Gov. Michelle Lujan Grisham is expected to sign into law a bill that will create a new Turquoise Alert System for missing Native Americans that will allow law enforcement to quickly share information through various communications channels…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Forrester is delighted to announce the opening call for our annual global Technology Awards in three categories this year: the Technology Strategy Impact Award, the Enterprise Architecture Award, and the all-new Data & AI Impact Award. These awards aim to recognize high-performing organizations that have enhanced business outcomes with their IT, AI, and data capabilities. (Links to submit your nomination based on your region are available at the end of this blog.) The Forrester Technology Strategy Impact Award The Forrester Technology Strategy Impact Award is the only award dedicated to recognizing excellence in IT strategy that continuously improves business results through the use of technology. We aim to highlight and reward organizations for enhancing business outcomes with their technology and IT capabilities, emphasizing alignment, trust, and adaptivity. This is the essence of high-performance IT. We invite nominations from companies that exemplify one or more of the following high-performance IT styles: Enabling capabilities: demonstrating excellence in stabilizing, operating, and protecting the business. Amplifying capabilities: utilizing automation, data and analytics, AI, and other technologies to optimize outcomes and drive business efficiency at scale. Cocreating capabilities: showcasing the rapid development, delivery, and operation of new products, features, or services. Transforming capabilities: scaling and rapidly deploying emerging technologies that create or disrupt new business models. Showcase how your IT strategy aligns with business goals, adapts to change, fosters trust, and improves business outcomes. Winning the 2025 Forrester Technology Strategy Impact Award offers prestige, significant exposure, and recognition for your organization’s achievements. The Forrester Enterprise Architecture Award The Forrester Enterprise Architecture Award is the only global awards program dedicated to recognizing excellence in enterprise architecture. We continue our partnership with The Open Group — author of the TOGAF® Standard, developed by The Open Group Architecture Forum — to co-judge the EA Award category this year. The recipients of this award can demonstrate their EA practice’s material contribution to their firms in managing risk, driving cost-efficiency, improving customer experience (including the employee experience), and increasing revenue (or supporting mission outcomes for nonprofit, governmental, and military organizations). They may also demonstrate: An EA roadmap that contributes to the high performance of the technology organization and the entire business. EA practices that drive change, growth, and differentiation through timely yet strategic decisions. An EA organization that embodies the six foundational priorities: valuable, influential, agile, accountable, innovative, and collaborative. EA metrics that focus on customer outcomes and experiences. This year, we continue our special award considerations with two categories: generative AI and platform engineering. We encourage all companies that have achieved success in outcome-driven EA practices to participate in the Forrester Enterprise Architecture Award. The Forrester Data & AI Impact Award The Forrester Data & AI Impact Award is designed to celebrate the impact of data, AI, and analytics initiatives that directly contribute to business results, especially in the backdrop of AI’s rapid pace of development. Newly empowered data, AI, and analytics leaders are meeting this challenge with innovative technology and intentional leadership approaches that solve today’s needs and set their enterprises up for the future. We want to recognize and honor their unique contributions at this critical juncture of technological change. The Data & AI Impact Award honors those remarkable enterprise data, AI, or analytics teams that catalyze effective decision-making to drive business outcomes. The winner will demonstrate the ability to: Deliver solutions at scale. Deliver data, AI, and analytics as a product for multiple enterprise functions, with demonstrable business results. Effectively enable stakeholders. Invest deliberately in driving literacy and competencies to amplify data, AI, and analytics across organizational objectives. Continuously build and maintain trust. Establish and maintain trust in data, AI, and analytics with effective frameworks and technologies. Nominations for the inaugural edition of this award will begin on Wednesday, April 23, 2025, and are only open for organizations based in North America. Who Should Apply? Nominations for the three award categories are open to organizations with 1,000 or more employees in sectors other than software or professional services that are executing a high-performance IT strategy and/or pursuing outcome-driven architecture as defined by Forrester. Technology leaders, including chief information officers, chief technology officers, chief digital officers, chief data officers, and enterprise architects, across three regions — North America; Europe, the Middle East, and Africa (EMEA); and Asia Pacific (APAC) — are encouraged to apply. (Note again that the Data & AI Impact Award is for North American organizations only.) Last year’s winners for the Technology Strategy Impact Award were Best Buy and First Student in North America, Smart DCC and BNP Paribas Bank Polska in EMEA, and Macquarie’s Banking and Financial Services group (Macquarie BFS) in APAC. For the Enterprise Architecture Award, the winners were Scotiabank in North America, DRÄXLMAIER Group in EMEA, and Contact Energy in APAC. You can find more information about the award categories, plus detailed submission packages and instructions, on the websites for our three Technology & Innovation Summits below. Please choose the appropriate link for your region: North America EMEA APAC Submissions close on May 27 for APAC and July 16 for North America and EMEA. We will notify the winners and finalists by the end of July 2025 for APAC and by the end of September 2025 for North America and EMEA. At that time, we will ask for additional information. We will then announce finalists and award recipients ahead of Forrester’s Technology & Innovation Summits in North America, EMEA, and APAC. Spread the word, and if you’re entering, good luck! source

00:00 Hi everybody, welcome to DEMO, the show where companies come in and show us their latest products and services. Today I’m joined by Tim Lawes—he’s the Senior Sales Director at SymphonyAI. Welcome to the show, Tim. 00:10Thanks for having me, Keith. 00:11All right, tell us a little bit about SymphonyAI and what you’re going to be showing us today. 00:14We’re a company with around 3,000 employees spread out across the world. We serve multiple industries, all built on AI technology. We have divisions for financial crime, retail and CPG, industrial, media, and I’m here representing the enterprise IT division. 00:35So, since the company name includes “AI,” I’m assuming you’re going to show us something related to artificial intelligence or generative AI. 00:49That’s a safe bet. The enterprise IT division is actually a backend platform designed for every employee to use. Regardless of company size, say you’re onboarding a new employee—that workflow process can go through our platform. So, from day one, that employee is using our backend system. The main users are IT service leaders—those handling tickets or internal requests. But it’s grown into what we call enterprise service management, because departments like HR and Finance also need to support employees. So, they all end up using our platform. 01:27Okay, so what’s the main problem you’re solving with this? Why should a company care? 01:33It’s really about driving efficiency. Think about onboarding an employee 10, 15, 20 years ago—that might’ve involved circulating emails or leaving sticky notes. Eventually, someone would forget the laptop, or the parking pass, and the new hire would sit idle for days. With our platform, it’s about modernizing those processes—adding workflows, and using generative AI to take it to the next level. 02:04This must require a lot of internal data. You can’t just take a consumer-grade generative AI tool and plug it in, right? 02:16Exactly. The sweet spot is integration. We want our generative AI copilot to connect with as much of a company’s tech stack as possible—up to where it makes sense. That way, it can run API calls across platforms. For example, if a company uses Workday as their HRIS system, we want to seamlessly push and pull data—handling onboarding, offboarding, promotions, insurance—everything in a streamlined way. 02:50You mentioned that without this, companies would rely on endless email chains. What else might they be doing? Would they be looking at other AI tools? What makes SymphonyAI unique? 03:08We’re a highly scalable platform. Sometimes when we enter a new sales cycle, the prospect may be using a competitor—but surprisingly, a lot of large companies don’t have a backend platform at all. They may rely on spreadsheets, shared inboxes, or patched-together tools from mergers and acquisitions. That’s where we come in—providing a single source of truth. Employees can go to one portal, or use our generative AI copilot via Microsoft Teams or Slack. It meets the employee where they work. That way, all departments and support groups use one platform. 03:57All right, let’s dive into the demo. You’ve got a couple of use cases to show us. 04:01Yep, for sure. I’ll start with our service portal and go through a basic end-user scenario. I’m based in Raleigh, North Carolina—and I had to travel here for this interview. Let’s say I’m a new employee and don’t know the travel policy. I can go to our copilot and ask, “How do I travel to Boston?”The copilot is like your best friend at work—the one who’s been there 20 years and knows everything. I can ask it, “I’m traveling to Boston for three days, what’s my travel per diem?” It tells me I have $60 per day (a bit skimpy with inflation!), and it also references our travel policy. It’s actually running an API call and pulling info from a 30– to 50-page PDF, summarizing just the relevant content. I can then continue a natural conversation: accommodations, regional info, etc. If I drop my laptop in a hotel parking lot, I can use Teams to file a service request. It’s the front-facing support tool for any employee. 05:35Let’s flip to the backend now. If I’m a support tech, and I get a ticket that Outlook isn’t working, our AI suggests how to triage it—suggesting workgroup, impact, urgency, assignment, and priority. That speeds up resolution time by getting tickets to the right hands faster. 06:02Now here’s an example of what we can do inside Microsoft Teams. The same capabilities exist in Teams, Slack, Google Chat—wherever conversations happen. Employees don’t need to go to a separate site, though they can if they want. But most of the value comes from meeting users where they are. 06:26Here, I asked the copilot to schedule a meeting with my colleague Jason Uri. It checked his Outlook calendar and returned two available time slots. I picked one, and it scheduled a Teams meeting automatically. 06:50You could’ve used this to book guests for this show! 06:53Exactly. This is just the first iteration. Soon, it’ll book flights, hotels—we’re calling it “AI for Work,” and it’s going to have a lot more functionality. 07:47Now, anytime companies use internal data with generative AI, there’s concern about hallucinations or security issues—like someone accidentally finding out the CEO’s salary. How do you prevent that? 08:15We take a security-first approach. Every customer gets a single-tenant architecture—no data is co-mingled. To access the system, you authenticate—like I did through Teams. The system inherits your roles and permissions. So, if I don’t have access in Workday to see CEO compensation, then the copilot can’t access it either. It uses your token to enforce those same permissions across integrations. 09:02So, how long does it take to install and integrate this? Are we talking six months? 09:12It’s actually very fast. We’ve got around 300 out-of-the-box connectors. The longest part is just figuring out what you want to do—where to plug it in, what problems you’re trying to solve. The platform uses Microsoft’s OpenAI LLM in our Eureka AI platform, so it’s ready to go on

Let’s start with some good news. According to Forrester’s Priorities Survey, 2024, business and technology leaders tell us that the number-one priority for their firm is to “improve the experience of our ultimate customers.” The top three priorities for this year are: 1. Improve the experience of our ultimate customers. 2. Meet measurable commercial growth targets. 3. Reduce costs. Improving customer experience (CX) is up from the third slot in 2023. That’s great, but it begs the question: How? Cross-Functional Journey Teams Are Here ( … Ish) We asked the respondents who said improving CX was a priority how they planned to do it, and almost a quarter said they are going to “create cross-functional teams aligned around customer journeys.” Cutting the sample by broad industry groupings backs up what we’ve heard from clients — firms in sectors like telecom, hospitality, utilities, and banking, which sell ongoing service-based “products,” are more likely to embrace cross-functional journey teams than industries like retail, where transactional channels can still dominate. We’ve published deep case studies on journey-centric organizations like E.ON, Lloyds, and Nissan. In a pair of recent reports we looked at how the banks that lead our Customer Experience Index (CX Index™) organize to improve the quality of their customer experience through two lenses, frontstage and backstage. The common theme is how these firms see helping customers achieve their goals as the focus of their organization — their marketing, their org structure, their budgets, their technology, their metrics, and more. Customers achieve their goals through journeys: We call this approach journey centricity. Understand The Three Stages Of Journey Evolution Journey centricity doesn’t happen overnight. The common threads in the case studies, as well as the wider research we’ve done, shows most firms progress through three distinct stages of evolution: Journey mapping to identify pain points and build foundational business cases for tactical action. Temporary project teams focus on pain points. This is where many CX teams stall. To break through, consider adopting the language of journey management, embrace increasingly available tooling, and infuse journey maps with data to elevate them from descriptive assets to living operational tools. Journey management to drive improvements and make the business case for transformation. As in some of the examples above, dedicated journey managers and journey teams begin to emerge, working cross-functionally to bridge silos in service of driving better customer outcomes. Navy Federal Credit Union maps and optimizes enterprisewide member journeys across product lines and business units. Journey centricity where journeys become the business operating model. Customer outcomes become the organizing principle behind teams, technology, budgets and operations. Rabobank organizes in value streams, such as mortgage, business lending, or daily banking. Journeys Connect Brand And Experience To Drive Growth At our CX Summit EMEA on June 2–4, 2025, we’ll be showcasing how brand and CX combine to create a total experience. Essentially, if your brand is the promise you make to your customers, your CX is your ability to deliver on that promise. Customers don’t interact with your brand in isolation, and (unless you’re Disney or Spotify, and even then … ) they don’t interact with you for fun. They come to you to achieve a goal. Journey maps help you understand those goals. Journey management helps you operationalize helping customers achieve those goals. Journey centricity aligns your organization around creating a total experience. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Reve AI, Inc., an AI startup based in Palo Alto, California, has officially launched Reve Image 1.0, an advanced text-to-image generation model designed to excel at prompt adherence, aesthetics, and typography. This marks the company’s first release, with future tools expected to follow. Reve Image is currently available for free preview at preview.reve.art, allowing users to generate images from text descriptions without requiring advanced prompt engineering. The company has not yet announced API access or long-term pricing plans, nor is it clear if the model will be proprietary or made open source, and if so, under what license. A new approach to AI imagery Reve Image differentiates itself by aiming for a deeper understanding of user intent. It allows users to not only generate images from text but also modify existing images with simple language commands. Example modifications include changing colors, adjusting text, and altering perspectives. The model also supports uploading reference images, enabling users to create visuals that match a specific style or inspiration. One of the model’s standout capabilities is its strong text rendering performance, addressing a common challenge in AI-generated imagery — and making it more directly competitive with text-focused image models such as Ideogram, which are more valuable to those designing logos and branding. Additionally, early user tests suggest that Reve Image handles multi-character prompts more effectively than previous models. Already topping the third-party benchmark charts Reve Image has already been evaluated by third-party AI model testing service Artificial Analysis. In the Artificial Analysis’s Image Arena, which ranks various image generation models based on user reviews and other quantitative metrics, Reve is currently in the lead at #1 for “image generation quality,” outperforming competitors such as Midjourney v6.1, Google’s Imagen 3, Recraft V3, and Black Forest Lab’s FLUX.1.1 [pro]. The benchmarking group highlighted Reve Image’s ability to generate clear and readable text within images, a historically difficult task for AI models. Before its official unveiling, Reve Image was known under the code name “Halfmoon” on social media, generating speculation and anticipation within the AI community. Merging human and AI understanding to create better, higher quality, more lifelike images Reve describes itself as a “small team of passionate researchers, builders, designers, and storytellers with big ideas.” The company is focused on developing creative tooling that enhances how users interact with AI-powered visuals. On X, Michaël Gharbi, Co-Founder and Research Scientist at Reve, shared insights into the company’s long-term vision, emphasizing the goal of building AI models that understand creative intent rather than merely generating visually plausible outputs. “Capturing creative intent requires advanced machine understanding of natural language and other interactions,” Gharbi said. “Our vision is to build a new semantic intermediate representation that both a human and a machine can understand, reason about, and operate on.” Other team members, including engineer Hunter Loftis and researcher Taesung Park, echoed the importance of bringing logic to AI-generated visuals. Park compared current text-to-image models to early large language models (LLMs), stating that they often produce visually appealing but logically inconsistent results. Early user reports show promise and limitations Early user feedback on the AI-heavy subreddit r/singularity (on Reddit), has been largely positive, with many praising the model’s accurate prompt following, high-quality text rendering, and rapid generation speed. Some users have reported success in generating multi-character scenes and complex environments, areas where previous models often struggled. However, some challenges remain. Users have noted that Reve Image: Struggles with certain complex objects (e.g., transparent materials like a full wine glass). Has difficulty recognizing specific fictional characters (e.g., users trying to generate characters from video games found the model produced more generic results). Occasionally misplaces details in multi-object compositions. Despite these hurdles, the team at Reve has been actively engaging with the user community and incorporating feedback into ongoing improvements. In my own brief hands on usage while drafting and creating the header image for this very article, I found Reve to be fairly intuitive and easy-to-use, with impressive visuals and prompt adherence. Like many AI-image generators, there’s a prompt entry textbox, though unlike Midjourney and Ideogram, Reve puts it at the bottom of the website and leaves your generated content up top to fill the majority of the space. In addition, the prompt entry textbox also contains four buttons below it for further fine adjustments to the image generation prompt sequence, including an aspect ratio adjuster (with standard sizing between 16:9 (widescreen landscape) and 9:16 (portrait, like a smartphone)… There’s another button selector for how many images you want to produce from each prompt (1, 2, 4, 8), a button to toggle on and off prompt text enhancement (it’s default toggled on, and this means that Reve will actually automatically edit the text you type in based on what it thinks you want to see in your image, adding lots more rich details and visual language than you might initially include) and a “seed” button for choosing if you want it to use a specific numeric string from a previous generated image to guide the generations going forward. It’s far fewer settings and doesn’t include any visual based editors like Midjourney, but the basics are there and it should be more than enough for most casual AI image users to get started. My brief tests also showed it was on-par or better than Ideogram at rendering legible text baked into images (and far surpassing Midjoruney), as well as on-par or exceeding the quality of rendering recognizable public figures as Grok (again, Midjourney and many other image generators prohibit this). What’s next for Reve image? While the model is currently only available via the company’s website, there is growing anticipation for API access or potential open-source options. Users have also expressed interest in additional features like custom model training, control tools for animation, and integration with creative software. For now, Reve Image remains freely accessible at preview.reve.art, allowing users to explore its capabilities

By Andrew Karpan ( March 21, 2025, 9:25 PM EDT) — Comcast and New York startup Touchstream Technologies Inc. said Friday they have reached a settlement in Touchstream’s $525 million infringement suit over video display patents. … Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Change isn’t just hard — it’s a continuous battle, and one that automation will make more intense and frequent. And if you think you’re prepared for automation’s pace of change that is coming, you’re already behind. We’ve barely grown comfortable with the past few years’ changes — remote work, video calls, hybrid chaos — and that’s just the warm-up. Take note from Forrester’s Automation Survey, 2024: 82% of companies are about to invest in generative AI (genAI), which will drown out the old ways of working. And here’s the kicker: The very teams deploying AI agents are admitting they don’t know how to manage the change they’re creating. Automation teams struggle with CM (change management) and admit it’s one of the biggest challenges of adopting automation. The Common Pain Points For Automation Initiatives Our new report, Change Management: Taming The Automation Beast, breaks down the challenges that automation decision-makers face and highlights how effective change management is more crucial than ever. Our analysis revealed the following CM concerns brought on by automation projects: Proving ROI. Change management initiatives related to automation projects require investment. Securing budget for these efforts can be challenging, as business leaders need to see ROI for change management itself. Employee retention, mental state improvements, and the value of ongoing skills development are hard to quantify. Job loss. Introducing new ways of working, especially automation, brings uncertainty and fear of job loss. In Forrester’s Future Of Work Survey, 2024, 39% of global workers said they fear losing their jobs to automation in the next 10 years. According to the customer service operations manager at a large manufacturing company, “Automation is perceived as a big threat … employees are not welcoming of change, and some view automation as an opportunity to reduce headcount.” Growing skill gaps. Ensuring that employees have the necessary skills to use automation and AI technology requires ongoing training. Many organizations lack proper training programs for nontechnical employees. Only 19% of global individual employees say they have been through formal training on how to use AI for work. As many employees are being given access to AI tools/AI agents, this poses a real challenge. Confidence And Trust In Change Management Is Missing Change management has a basic problem. Top-level executives report a high degree of confidence in their CM practices, yet employees believe the opposite: CM initiatives are inadequate. Employees lack confidence in CM practices and lack trust in their organization’s leaders. What this means is simple: Folks in charge of implementing CM are not trusted to follow through on promises. Employees would like CM to be more integrated into leadership responsibilities. However, without addressing this chasm of confidence and trust, it is unlikely to work. It’s Time To Bring Your Change Management Up To Speed The accelerating pace of automation demands that traditional CM methods adapt to its speed and impact. You first need to address your organization’s AIQ (the AI quotient), which measures the readiness of individuals, teams, and organizations to adapt to, collaborate with, trust, and generate business results from genAI and other forms of AI. You then need to focus on Change Management: Taming The Automation Beast. This report highlights the following key areas for automation teams to prioritize: clear communication around pending automation, giving them more control over automation that impacts their work, and adopting an iterative and continuous CM approach. source

Wise also discussed data quality, and the cultural shift to deliver and continuously improve on technology excellence. Watch the full video below for more insights. On achieving efficiencies: When you come into a pre-IPO environment, there’s a lot of fast growth. And there’s a lot of situations where your business processes aren’t really as mature as they should be. And because of speed, maybe you’re doing things that are manual but you have to start maturing because end-to-end processes have to be as efficient as possible. So Automation Domination is a program we put in place to change the way the company thinks about efficient automation of processes and not accepting the status quo. We made it a top level company objective and the key result was to save 67,000 manual people hours. The way we came up with that was we took our employee base, about 1,200 employees, and asked, what if we could save one hour per week per employee for the entire year? So that’s the rough math of why 67,000 hours became the goal. The real deliverable, though, was to change the culture and the way people think about what they’re doing. It was also to create an environment where people also thought about what they do and how it affects other groups. On outcomes: Automation Domination breaks down silos and becomes ingrained into our environment. Then for me as a CIO, I know there’s going to be process improvement, efficiencies, and speed that ultimately help our customers. So we focused a lot on the sales and marketing. It was a great experience and it was so successful that we’re doing it again and our next goal is to save 100,000 hours. It’s a pretty awesome experience and now it’s changed the entire culture so I don’t have to cheerlead anymore. You just hear team members and employees talking about it all the time. source