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While genAI has been a hot topic for the past couple of years, organizations have largely focused on experimentation. In 2025, that’s going to change. It’s the year organizations will move their AI initiatives into production and aim to achieve a return on investment (ROI). But first, they’ll need to overcome challenges around scale, governance, responsible AI, and use case prioritization. Here are five keys to addressing these issues for AI success in 2025. 1. Identify your top genAI use cases. For organizations seeking productivity and innovation gains, a best practice is to prioritize use cases based on value, feasibility, and breadth. To determine value, ask yourself questions like: How strategic is this use case? Does it contribute to business outcomes such as revenue, sustainability, customer experience, or saving lives? To evaluate feasibility, ask: Do we have internal data and skills to support this? What are the associated risks and costs, including operational, reputational, and competitive? Finally, when evaluating scope or breadth, go broad when there’s competition for resources and narrow if there’s hesitation toward adoption. 2. Evaluate processes that can be improved with genAI. When thinking implementation, first consider how genAI can improve existing business processes. Next, explore potential new workflows or processes that genAI can create to improve productivity, increase innovation, and/or provide competitive differentiation. 3. Prioritize data quality and security. For AI models to succeed, they must be fed high-quality data that’s accurate, up-to-date, secure, and complies with privacy regulations such as the Colorado Privacy Act, California Consumer Privacy Act, or General Data Protection Regulation (GDPR). Adhering to these practices also helps build trust in data. That said, watch for data bias. Put robust governance and security practices in place to enable responsible, secure AI that can scale across the organization. 4. Invest in internal or outsourced skills. Like any new technology, organizations typically need to upskill existing talent or work with trusted technology partners to continuously tune and integrate their AI foundation models. The same holds true for genAI. Organizations should create a cross-functional team comprised of people who are already building, managing and governing existing AI initiatives in order to lay the foundation for genAI and select the appropriate AI solutions or models. 5. Increase adoption through change management. Driving genAI adoption requires organizations to incorporate it into company culture and processes. Change management creates alignment across the enterprise through implementation training and support. Find a change champion and get business users involved from the beginning to build, pilot, test, and evaluate models. Ask for input on challenges and needed efficiencies and provide credit for employee contributions. 6. Track ROI and performance. GenAI operations and business automation teams must look at value and complexity against cost to determine which use cases provide the highest return for their investment. The goal should be to use lower-cost automation technologies and low-code platforms when possible, and genAI as needed. When it comes to performance, the KPIs for business processes are the same with AI-enhanced improvements. Some of these include: greater efficiencies and productivity around process improvements, faster cycle times, higher customer satisfaction, and market share gains through innovation. Work with expert partners Many organizations struggle to ensure successful AI and genAI implementations. That can be due to a lack of skillsets, concerns about risks or integration complexity, or identifying the right use case that will deliver ROI. Turn to experts for guidance and support. Ask how you can customize genAI to meet organization’s needs and ensure business value. For example, Argano works with companies across industries to design and deploy AI and genAI solutions that streamline operations, increase agility, and drive sustainable growth. Consultants can help you develop and execute a genAI strategy that will fuel your success into 2025 and beyond. Click here to learn more about how you can advance from genAI experimentation to execution. source

Customer experience (CX) is how organizations win, yet the path to that success is far from straightforward. A variety of touchpoints, non-linear journeys, changing preferences, and behaviors make it tricky to deliver a consistent, end-to-end experience. This is where customer journey orchestration becomes vital, allowing companies to navigate these complexities and turn customer experience into measurable outcomes. Customer journey orchestration involves analyzing customer behavior across all channels and touchpoints to strategically coordinate the overall experience. This comprehensive view of the customer journey signposts the way for companies to deliver relevant personalization that deepens connections and demonstrates a true sense of intimacy. Investing in this approach pays off significantly: on average, organizations that excel in customer journey orchestration see revenue increases of 10-20%, cost savings of 15-25%, and improvements in customer advocacy scores of 20-40 points. Here’s what you need to know. Customer journey orchestration is a top priority for 2024 and beyond  A recent report from Gartner highlights customer journey orchestration as a crucial area of CX focus. Nearly 60% of customer service and support leaders plan to invest within the next 12 to 18 months to gain a deeper understanding of customer needs throughout the entire buying journey. Right now, this is a key challenge hindering their ability to improve the customer experience without a cohesive view of behavior across touchpoints. The closer the customer connection, the bigger the gains Customer journey orchestration works by first developing a comprehensive profile for each customer that includes demographic information, behavioral data, transactional history, channel preferences, and more. This holistic view allows companies to look at the buying journey in its entirety instead of just pieces of it. This foundational understanding cultivates a deeper connection with customers, enabling businesses to grasp how each person moves through their journey, why they make certain choices, and how to effectively engage them at the right moments for desired outcomes. Companies that excel in this level of orchestration see significantly faster growth, deriving 40% more of their revenue from these efforts compared to their slower-growing counterparts. Just as importantly, you’ll be able to quickly identify shifts in customer behaviors. Research shows that 75% of customers try a new shopping behavior each year. Customer journey orchestration provides a solid framework for understanding these changes, helping companies navigate shifting behaviors and meet new needs.  Use case: Customer journey orchestration in action After analyzing six months’ worth of data gathered from various sources like their electronic health record (EHR) system, patient surveys and feedback forms, appointment scheduling and attendance records, and patient interactions on their health portal and mobile app, Healthcare Co. noticed a few things. A rising trend in appointment cancellations, specifically among patients under 30 for their annual well exam. Further analysis shows that many of these patients cite scheduling conflicts or lack of reminders.  Patients who receive proactive communication and preventive screenings (like flu shots, for example) are more likely to schedule those appointments. For patients under 30, the preferred channel is SMS/text message. An uptick in the use of telehealth services for non-urgent issues, especially on evenings and weekends.  Armed with this knowledge, the organization implements automated reminders via text and email, specifically targeting younger patients who are canceling appointments. They also develop a personalized proactive outreach campaign to remind patients about preventive care services, doubling down on SMS to increase engagement. They also decide to expand availability of telehealth appointments during weekends and evenings to help make service more accessible for patients.  Using customer journey orchestration, the provider can drill down into this customer segment, connecting them with the information they need on the channel that works best for them – improving efficiency, reducing cancellations, and helping minimize costly no-shows.  3 key benefits for customers  Personalization, speed, and consistency are the reigning trio of customer experience: Seventy-one percent of customers expect companies to deliver personalized interactions, and 76% get frustrated when it doesn’t happen. Two-thirds of customers say speed is as important as price and more than half will hire the first business to respond to their requests, even if it’s more expensive. Most customers say they can feel when a company’s different departments like sales, service, and marketing are disconnected.  Customer journey orchestration is designed to tick every box, ensuring you provide real-time personalization, rapid response times, and seamless interactions across all touchpoints and channels.  Customer journey orchestration made easy Customer experience is about getting a complete picture of each customer at every step of their buying journey to demonstrate a sense of intimacy that research shows leads to higher satisfaction and generates faster rates of revenue growth. Customer journey orchestration sounds complicated, but it doesn’t have to be. Avaya makes it easy for enterprises to prioritize customer journey orchestration using simple contact center plug-ins. Show us what you have, and we’ll show you how to unlock its full potential.  Visit our website to see how Avaya and its solutions empower enterprises to embrace customer journey orchestration. source

View data as a shared asset. A modern data architecture needs to eliminate departmental data silos and give all stakeholders a complete view of the company: 360 degrees of customer insights and the ability to correlate valuable data signals from all business functions, like manufacturing and logistics. Provide user interfaces for consuming data. Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data. Ensure security and access controls. Modern data architectures must be designed for security, and they must support data policies and access controls directly on the raw data, not in a web of downstream data stores and applications. Establish a common vocabulary. Shared data assets, such as product catalogs, fiscal calendar dimensions, and KPI definitions, require a common vocabulary to help avoid disputes during analysis. Curate the data. Invest in core functions that perform data curation such as modeling important relationships, cleansing raw data, and curating key dimensions and measures. Optimize data flows for agility. Limit the times data must be moved to reduce cost, increase data freshness, and optimize enterprise agility. Data architecture components A modern data architecture consists of the following components, according to IT consulting firm BMC: Data pipelines. A data pipeline is the process in which data is collected, moved, and refined. It includes data collection, refinement, storage, analysis, and delivery. Cloud storage. Not all data architectures leverage cloud storage, but many modern data architectures use public, private, or hybrid clouds to provide agility. Cloud computing. In addition to using cloud for storage, many modern data architectures make use of cloud computing to analyze and manage data. Application programming interfaces. Modern data architectures use APIs to make it easy to expose and share data. AI and machine learning models. AI and ML are used to automate systems for tasks such as data collection and labeling. At the same time, modern data architectures can help organizations unlock the ability to leverage AI and ML at scale. Data streaming. Data streaming is data flowing continuously from a source to a destination for processing and analysis in real-time or near real-time. Container orchestration. A container orchestration system, such as open-source Kubernetes, is often used to automate software deployment, scaling, and management. Real-time analytics. The goal of many modern data architectures is to deliver real-time analytics — the ability to perform analytics on new data as it arrives in the environment. Data architecture vs. data modeling According to Data Management Book of Knowledge (DMBOK 2), data architecture defines the blueprint for managing data assets as aligning with organizational strategy to establish strategic data requirements and designs to meet those requirements. On the other hand, DMBOK 2 defines data modeling as, “the process of discovering, analyzing, representing, and communicating data requirements in a precise form called the data model.” While both data architecture and data modeling seek to bridge the gap between business goals and technology, data architecture is about the macro view that seeks to understand and support the relationships between an organization’s functions, technology, and data types. Data modeling takes a more focused view of specific systems or business cases. source

00:00 Hi everybody, welcome to DEMO, the show where companies come in and they show us their latest products and platforms. Today, I’m joined by Neil Miller, he is the Director of Product Marketing at Kissflow. Welcome to the show, Neil. So tell us a little bit about what Kissflow is, and then what are you going to show us here today? 00:14So Kissflow is a no-code, low-code, application platform that really spreads the power of application development across the enterprise. 00:21Generally, who is this designed for? Is it designed for product developers, or is it other people within the company that might not be a developer? 00:30Yes, so Kissflow is a unique product in that it’s really built for both groups, so it can handle the people that like the high-powered, low-code developers who really want to build a lot of things out — they don’t need a lot of certifications or anything. It’s a platform they can get on to build things very quickly and easily. But then the other side, you also have junior developers, business analysts and specifically process owners, who want to build their own thing themselves. The platform is easy enough for them to use that they can build their own applications too. 00:56Do you subscribe to the whole citizen developer movement that we’re seeing in the space, because of skill shortages and things like that? 01:04Absolutely. Citizen development is one of the main themes we like to play into. Now our platform is very governed, so IT admins have the ability to govern the entire platform and know what’s going on in there. But at the same time, we believe that people who actually run these processes probably know best what’s there. So as long as you give them the right tools, and you give them enough training, they’re able to build what they need. 01:25Because I guess if I was in IT, the biggest fear would be like, “Wait, you’re we’re giving power to who?” Because the last thing you want is me programming something, with very little design or development skills. So why should companies care about Kissflow versus maybe some of the other platforms out there, or some of the other processes that go on. 01:42Like I said, Kissflow’s unique thing is that one, it’s just super easy to use. You’re going to see it in the demo here a second. The layout, the feel of it, is just really geared towards someone who knows what they want but maybe doesn’t have the development skills about it. There’s a lot of things we won’t show today that show the power of the low-code side of it as well, so that even a higher-powered developer can come in and really do what they want to do, but that’s one thing that really makes it easy, is just the ease of use and be able to generate things quickly. So even somebody who’s in the IT department that just wants to build a lot of apps very quickly to get things out of their backlog, they can really easily build dozens of apps on this. 02:16If companies didn’t have this, would they just be relying on developers to do a lot of the requests that are coming in? Does this offload some of those processes to people that usually don’t have those skills? 02:26So a few different things. One is that they would either just be custom developing things. Second is they might be using a different low-code platform, but typically, you’re only going to be building two or three applications a year on those really big platforms that are out there. Kissflow is more like, “Hey, give us a few dozen that we’re going to get done in a year.” Then the citizen developers, the other thing they would be using would just be spreadsheets, Excel or something like that, to build what they need. So this is their option to actually get something that’s an improvement on Excel. 02:53So let’s go into the demo. Tell us what you’re going to show us. 03:00What you see here is the basics of a process. So we have a few different modules in Kissflow, but the process builder is one of the easiest to understand, and the one that generates the most interest for most people. So we start off with a form, which is a little bit interesting. Most people are going to say, OK, build us a data table or something like that. But we actually want to start with a form, because that’s where the process owner is usually going to start. They know what they want to do. In this situation, we’re looking at asset disposal requests. So this is, again, something maybe your admin team is going to use, or maybe somebody else in the IT department is going to use, but it’s really something that the person who is building this knows what they need, and they just want to be able to bring that in. So the form is very, very simple. It’s all drag and drop. We have tons of form fields that are available here on the left, all sorts of things, from very simple things to very complicated. We also have some AI features here. So if you want to, just based on the name asset disposal request, you’re going to be able to generate types of fields you might need to know. So if somebody’s building it for the first time, they’re going to be able to bring those in. They can do anything here, building out sections, you’re also able to refer back to fields. We have remote lookup, so you can go to databases outside of Kissflow and bring those things in. Every field has the ability to change the settings, to add validations, add visibility requirements, stylize it the way you want, and even add these custom events, which is more the low-code part of what’s going on. So the field, the form is one of the things that is most

In what can only be labeled as a very encouraging trend, jobs and projects abound for tech professionals wanting to use their skills and expertise to try and make our planet and climate well again. These opportunities fall under the umbrella category of climate technology and involve full-time careers, part-time jobs, and volunteer opportunities. One of the fastest-growing industries in the world, climate tech — and its companion area of nature tech — require a wide range of skills to help solve significant environmental problems. In especially high demand are IT pros with software development, data science and machine learning skills. Projects needing the most IT job and skills help Climate tech professionals can lend their skills and talents in a wide range of areas, explains Kanani Breckenridge, CEO and “headhuntress” at Kismet Search. She works with commercially focused companies developing technologies to support and boost projects and products that impact multiple sectors within greentech. In the U.S., common projects for climate tech professionals are related to EV infrastructure (solar, wind, and nuclear projects), smart grids, and corporate carbon tracking analytics — which is fueled in a large part by government subsidies and funding, Breckenridge explains. In Europe and some other regions, the priority is often with projects related to smart cities, circular economies, and renewable energy integration. Water management projects are more dominant in water-scarce regions, Breckenridge says. She notes, however, that the green sector has a lot of overlap globally as climate and sustainability goals become increasingly universal. While crucial, if organizations are only monitoring environmental metrics, they are missing critical pieces of a comprehensive environmental, social, and governance (ESG) program and are unable to fully understand their impacts. IDC’s Sustainability Readiness Survey 2024 shows that the top 2 areas of ESG/sustainability-related investment for organizations are IT infrastructure efficiency assessments and investments (cited by 41.9% of survey respondents) and circular economy implementations (40.2%). Industries and sectors where the jobs are most plentiful Organizations hiring IT professionals in the climate and greentech space include renewable energy companies (such as solar and wind providers), greentech and agritech startups developing innovative sustainability solutions, and corporate sustainability teams in large organizations focused on reducing carbon footprints, Breckenridge says. Government agencies and nonprofits also seek IT talent for environmental data analysis and policy development. Additionally, nuclear power companies and energy infrastructure firms are hiring to optimize and secure energy systems, while smart city developers need IoT and AI specialists to build sustainable and connected urban environments, Breckenridge explains. In the climate and green sector, IT pros are the backbone of innovation across multiple areas, Breckenridge says. Some of the most common IT needs per specific sector within the broader climate technology space, according to Breckenridge, are: “Renewable energy companies need cloud engineers and data scientists to make smart grids work and integrate renewables like wind and solar.” “Agritech firms are hiring IoT and AI experts to streamline farming — think smart irrigation and predictive crop analytics.” “In the EV and battery space, software engineers and product managers are driving the build-out of connected charging networks and improving battery life.” “Greentech startups and corporate sustainability teams are bringing in AI talent to track carbon emissions and cut waste.” “Government agencies and nonprofits are looking for data scientists and engineers to help with climate modeling and environmental impact analysis.” Breckenridge points out that cybersecurity professionals are also important across all sectors because “securing all this critical infrastructure is just as important as building it.” The tech professionals most in demand The most in-demand technical skills in the climate and greentech sector revolve around cloud computing, data analytics, IoT, and cybersecurity — each playing a critical role in driving sustainable innovation, Breckenridge explains. She breaks down the skills demands as follows: Cloud architects/engineers: Cloud platforms skills with AWS, Microsoft Azure, and Google Cloud are essential for managing the massive datasets generated by renewable energy grids, smart cities, and sustainability projects. IT professionals with expertise in cloud architecture and optimization are needed to ensure these systems are scalable, efficient, and capable of real-time environmental monitoring, Breckenridge says. Data scientists and AI/ML engineers: These skills are in high demand, since large-scale data analytics that drive decision-making are also key to efforts related to sustainability, Breckenridge explains. Skills in Python, R, TensorFlow, and Apache Spark enable professionals to build predictive models for energy usage, optimize resource allocation, and analyze environmental impacts. This is where machine learning algorithms become indispensable for tasks such as predicting energy loads or modeling climate patterns. Companies that are also typically associated with more legacy/non-climate-friendly energy such as oil and gas and mining are also utilizing analytics to optimize efficiencies. Edge device (IoT) engineers: Those skilled in protocols such as MQTT and LoRaWAN, and tools such as Azure IoT and Google IoT Core, are building connected devices that manage everything from smart grids to water conservation, Breckenridge says. These systems collect real-time data to optimize energy distribution, reduce waste, and monitor environmental conditions, making IoT a core piece within smart and sustainable infrastructure. Cybersecurity engineering specialists: With all this digital innovation comes a growing need for cybersecurity engineering skills, especially related to critical infrastructure such as energy grids and EV charging networks, Breckenridge says. As they become increasingly digital, securing these systems is critical for preventing potentially disastrous outages and events. Cybersecurity experts fluent in tools such as those from Palo Alto Networks, Cisco, and Splunk are vital for protecting against cyberattacks and ensuring the resilience of sustainable systems. DevOps and software engineers: To build out infrastructure and applications, DevOps and software engineering skills are critical for making the solutions that drive/support climate efforts and tech, Breckenridge says. Proficiency with tools such as Kubernetes, Docker, and Jenkins enables teams to build and deploy these solutions to make sure these systems can scale. ESG skills becoming a must-have at some organizations As organizations and government agencies face increasing pressure to meet sustainability goals, knowledge of ESG reporting tools is becoming a must-have in many IT

Overview In an exclusive interview with Khalid Saad Al Medbel, a leading cybersecurity expert from Saudi Arabia, we dive into the pressing issues and evolving trends shaping the cybersecurity landscape today. With years of experience navigating the complexities of digital security, Al Medbel offers valuable insights into the challenges facing Chief Information Security Officers (CISOs), the significant trends of 2024, and the role of artificial intelligence in shaping modern cybersecurity strategies. As cyber threats continue to grow in sophistication, his perspectives on the intersection of technology and security provide an in-depth look at how organizations are adapting and evolving their defenses in an increasingly digital world. Register Now source

Ownership wars of the largest-ever economic engine Inbar pointed out that in the AI world, there is no “fair” competition or second-best — it’s a winner-take-all situation. “Imagine a race to get up and down a slide,” he said. “The first to get to the top of the slide may be just inches ahead of the others, but the moment they start sliding, the gap opened is so much larger than the inches at the top that it is impossible to catch up any more.” Going for-profit will help OpenAI maintain superiority, with stable funding from shareholders, he noted. On the other hand, though, the public will no longer be able to benefit from, contribute to, or influence AI development. source