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5 Tips For A Successful AIOps Deployment

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  • By Ranjith Lewis and François Habryn 

    Successful technology modernization projects are driven by people and processes. Yet all too often, companies spend the majority of their time and resources acquiring digital tools rather than promoting organization-wide acceptance of the new technology.

    Overlooking the human element inherent in digital innovation can undermine almost any transformation initiative. Roughly 70% of change programs fail to achieve their goals due in large part to employee resistance, lack of management support, and other "soft costs" of organizational change, according to McKinsey. As a result, investments in technology that are designed to improve customer satisfaction, enhance internal operations, or advance other corporate objectives tend to yield costly overruns, low adoption rates, and poor business outcomes.

    There's a better way.

    When planning any large-scale digital innovation or a new way of working, think strategically about the nontechnical aspects of the initiative. Building awareness, gaining buy-in, and reinforcing change throughout your organization pave the way for a much smoother journey than focusing on the technology alone.

    Experience offers proof. These five tips—learned through helping scores of customers deploy artificial intelligence operations (AIOps) across their organizations—can help put your company on the right path to successful technology implementation.

    1. Humanize your approach. As an emerging technology, AI is often mistrusted and misunderstood. Some in the workforce fear it could make their roles obsolete—but it's more likely to help people supercharge their capabilities. Your employees must trust the new technology before they can use it to make informed decisions or produce specific results.

    Insights generated by AIOps can automatically predict emerging issues with a high degree of certainty. When your teams grow comfortable with machine-generated insights, they can investigate anomalies and resolve related issues before they experience service disruptions or other problems.

    It's a fundamental shift in operational thinking to move from a reactive model that measures mean time to detect and mean time to repair (MTTR) to a predictive strategy that gauges mean time before failure and mean time between failures. That's why, when deploying initiatives like AIOps, you need to consider how it will affect your people and processes after implementation.

    If you or your employees need assurance about the effectiveness of a technology, start your modernization journey with an experiment. With AIOps, you might continue responding to incidents after they arise, as you normally would, while using AIOps following remediation to investigate underlying causes of the disruptions. The resulting data from this use case shows how insights about some anomalies can help you predict changes in operational performance.

    After formally implementing technology that's backed by positive outcomes, seek out and incorporate employee feedback. Make a point to:

  • Solicit comments and answer questions from users.
  • Diagnose and address any post-implementation issues.
  • Celebrate successes and team engagements.
  • Involving employees throughout the process and continually refining the new ways of working help foster goodwill and bolster adoption throughout your organization, leading to sustained progress.

    2. Secure executive sponsorship. During the planning stages of technology modernization, your CIO, CTO, and other executives must align the transformation goals with your organization's overall business strategy. This unified vision helps IT leaders engage their teams and prepare practitioners for change.

    Once executive sponsorship is in place, identify advocates within your company who will drive change daily. These individuals need to champion modernization among their colleagues, highlighting the benefits the new technology can deliver.

    In the AIOps case, three roles are particularly important:

  • Site reliability engineer: Determines business needs, putting software and systems in place to promote adoption
  • Operations leader: Ensures teams remain committed to the implementation strategy and full technology adoption
  • Data engineer: Builds a flexible and scalable AIOps architecture 
  • After the implementation begins, your executive team needs to continue providing direction and support. Their ongoing leadership is vital to improving buy-in and usage rates throughout your company.

    3. Communicate reasons for change. If employees at every level appreciate why your company is deploying new technology like AIOps, they may be more receptive to change. Put the journey in perspective by:

  • Outlining operational value and business opportunities, such as enhanced customer experiences
  • Showing how the change aligns with organizational and IT strategies
  • Explaining why it's the ideal time to implement enhanced technology
  • Detailing ways innovation can improve their employee experience and productivity
  • Consistently promoting these messages helps increase employee buy-in and acceptance across your organization.

    4. Implement changes incrementally. Employees will either embrace or resist modernization based on how useful they perceive the technology to be. A phased adoption helps demonstrate the value of transformation.

    In the AIOps scenario, first apply the technology to a single use case. After achieving positive results with one data source and a defined area of scope, begin introducing AIOps in additional environments using multiple sources and larger amounts of data.

    A methodical approach helps your team gain confidence in AIOps-enabled decision making and the technology's ability to automatically deliver insights, after which the team can move to more complex implementations—while also coming to realize that AIOps is intended to augment employee capabilities, not supersede their expertise.

    5. Measure and reward. During periods of major change, employees can be highly motivated by how they're measured and rewarded. Results from numerous AIOps deployments confirm that technology adoption rates increase when project and organizational change teams and executive sponsors work together to:

  • Demonstrate business impact at the departmental level, such as with a reduction in application downtime and customer incidents, which helps facilitate company-wide adoption.
  • Develop incentive programs to recognize employees when they reach select milestones, such as a reduction in tickets and incidents, MTTR, or service and application availability.
  • Measure post-implementation engagement and adoption rates across your organization as part of daily workflows.
  • No two technology modernizations are the same. However, successful AIOps deployments of every size and scope support one widely applicable lesson: regardless of your IT initiative, user-focused thinking drives greater business outcomes.

    Learn how Kyndryl can help with your AIOps deployments and download our white paper Defining the Journey to AIOps.

    Ranjith Lewis is chief technology officer at Kyndryl Denmark. François Habryn is associate partner for cloud, applications, data, and AI at Kyndryl Switzerland.


    AIOps Platform Market Accelerates Towards An US$ 80.2 Billion Valuation By 2032, Driven By A Resilient 25.4% CAGR Surge

    According to the AIOps platform market analysis carried out by Future Market Insights (FMI), the demand registered in the AIOps platform market will grow at a noteworthy CAGR of around 25.4% from 2022 to 2032.

    The report states that the market is expected to reach a valuation of US$ 8.3 Billion by the end of 2022 and US$ 80.2 Billion by 2032. As per Future Market Insights, the pandemic is anticipated to encourage the market growth of emerging tech fields, such as artificial intelligence, as a result of the required work-from-home policy.

    The AIOps platform automates routine IT operations using intelligent, self-learning algorithms supported by ML. Through the use of behavioral and historical data analysis, it also recognizes and foresees any potential incidents.

    Request a Sample Report to Learn about Recent AIOps Platform Market:https://www.Futuremarketinsights.Com/reports/sample/rep-gb-15657

    Furthermore, it offers a cognitive examination of the data using big data analytics and extracts relevant information from the data for further processing. Real-time data integration, multi-dimensional data normalization, extremity-based issue prioritization, and documented response strategies to avoid recurrences are all made possible by combining IT operations with AI. This capacity for creating actionable insights from raw data contributes to the development of a flexible ITOps architecture.

    A group of algorithms created specially to operate in the AIOps field. They are employed to automatically find, identify, and fix problems in the cloud infrastructure. As new technologies develop and in accordance with the operational objectives and data of business that AI is intended to optimize. For effective performance monitoring of IT operations, organizations are predicted to keep implementing AIOps platform solutions. This has propelled the growth of the AIOps platform market.

    Key Takeaways: AIOps Platform Market

  • By solution, the AIOps platform segment accounts for the highest market share of around 61.2% for AIOps platform market in the year 2021. However, the services segment is estimated to grow at a robust CAGR of 26.2% through 2032.
  • By application, the real-time analytics segment had the highest market share of around 39.9% in the AIOps platform market in 2021.
  • By vertical, the IT & telecom is predicted to grow at a CAGR of around 28.5% between 2022 & 2032.
  • By region, North America had the largest market share of around 35.6% in AIOps platform market in 2021, whereas the South Asia & Pacific region is showing the highest growth of around 29.6% CAGR during the forecast period.
  • Rapid adoption of the cloud-based infrastructure, demand for AI based application is surging and increasing need for risk mitigation and rise in data volumes in IT organizations.

    DevOps systems have evolved to be smarter for seamless and efficient business operations as IT technologies and devices have, leading to an increase in the usage of AlOps. The operational risks associated with cloud migration and a hybrid cloud strategy can be significantly decreased using AIOps. It serves as a monitoring tool for virtualization, storage, and cloud infrastructure, reporting on parameters including consumption, availability, and response times.

    By integrating them into AIOPs platforms, businesses are replacing several traditional monitoring tool categories. For instance, AIOps platforms are used only for virtual network monitoring, observability, and infrastructure as a service (IaaS) monitoring, particularly if the organization has its whole IT infrastructure in the cloud.

    Furthermore, as more organizations switch to digital platforms for their operational requirements, automation using AI becomes more realistic and affordable for their organization, opening up new opportunities for their business. As a result, rise in data volumes and its resulting increase in cloud adoption will probably lead to an increase in the demand for AlOps platforms.

    Seize this Opportunity: Buy Now for a Thorough Reporthttps://www.Futuremarketinsights.Com/checkout/15657

    More Valuable Insights:

    Future Market Insight's report on AIOps platform market industry research is segmented into four major sections – solution (AIOps platform, and services (implementation services, license & maintenance services, training & education services, others), application (real-time analytics, application performance management, infrastructure management, others), vertical (BFSI, healthcare & life sciences, retail & consumer goods, IT & telecom and others), and region (North America, Latin America, Europe, East Asia, South Asia & Pacific, and The Middle East & Africa), to help readers understand and evaluate lucrative opportunities in the AIOps platform demand outlook.

    AIOps Platform Market Segmentation:

    By Solution:

  • AIOps Platform
  • Services
  • Implementation Services
  • License & Maintenance Services
  • Training & Education Services
  • Others
  • By Application, AIOps Platform Market is segmented as:

  • Real-Time Analytics
  • Application Performance Management
  • Infrastructure Management
  • Others
  • By Vertical:

  • BFSI
  • Healthcare & Life Sciences
  • Retail & Consumer Goods
  • IT & Telecom
  • Others
  • By Region:

  • North America
  • Latin America
  • Europe
  • East Asia
  • South Asia & Pacific
  • Middle East and Africa (MEA)
  • About Future Market Insights (FMI):

    Future Market Insights, Inc. (ESOMAR certified, recipient of the Stevie Award, and a member of the Greater New York Chamber of Commerce) offers profound insights into the driving factors that are boosting demand in the market. FMI stands as the leading global provider of market intelligence, advisory services, consulting, and events for the Packaging, Food and Beverage, Consumer Technology, Healthcare, Industrial, and Chemicals markets. With a vast team of over 5000 analysts worldwide, FMI provides global, regional, and local expertise on diverse domains and industry trends across more than 110 countries.

    Contact Us:        

    Nandini Singh Sawlani   

    Future Market Insights Inc.Christiana Corporate, 200 Continental Drive,Suite 401, Newark, Delaware – 19713, USAT: +1-845-579-5705For Sales Enquiries: sales@futuremarketinsights.ComWebsite: https://www.Futuremarketinsights.ComLinkedInTwitterBlogsYouTube


    The 10 Most Powerful Companies In Enterprise Networking 2023

    What makes these 10 vendors of network gear the biggest power players? They're stalwarts of LAN and WAN infrastructure, delivering network-centric security technologies and shaping the future of AI networking.

    It's been the year of AI, and expectations are high as enterprise network vendors begin to deliver on the promise of AI networking. Industry players have long been touting the benefits of AI-based operations (AIOps) to help resource-constrained network teams troubleshoot and remediate performance issues, and modern network services such as SD-WAN, 5G and SASE rely on AI to automate some network provisioning and security tasks. Now the release of Microsoft-funded ChatGPT has elevated AI to a C-level imperative, and AI innovation is heating up.

    Everyone is jumping on the bandwagon. Nvidia is cranking out GPUs for AI workloads at a record pace, and the hyperscalers are gobbling them up to enhance their AI offerings. Enterprises are racing to embed AI functionality throughout their on-prem and cloud infrastructures. For enterprise network vendors, there's an opportunity to deliver products and services with an extra helping of generative AI smarts.

    On a more fundamental level, those GPUs need to move incredible amounts of data, which creates demand for high-performance interconnects. InfiniBand is commonly used for high-performance computing, but Cisco, Arista, Broadcom, HPE and others have created the Ultra Ethernet Consortium with the goal of making Ethernet the industry standard for AI networking.

    The 10 power players on this list are able to deliver highly mature offerings in areas of LAN and WAN infrastructure and services, have a strong security play, and are positioning themselves to take full advantage of the AI boom.

    Editor's note: Our list is ordered, with input from industry watchers, to reflect the companies that are making the biggest power moves and the broadest impact on the network industry. We've evaluated these companies not by size but by their influence in the market and their forward momentum. In other words, there is some subjectivity associated with this list.

    1. Cisco: Plunks down cash for Splunk

    Why they're here: When you're the dominant vendor in your market seemingly forever, there might be a tendency to get complacent. Not Cisco under CEO Chuck Robbins. Cisco shook up the networking world with the announcement in September that it plans to buy SIEM stalwart Splunk. Robbins explained that integrating Splunk's sophisticated data analytics capabilities will bolster Cisco's AI push. The company reported that it has already taken $500 million in orders for AI Ethernet fabrics, mostly from hyperscalers, and sees the potential for much more. Overall, Cisco continues to run on all cylinders - Ethernet switch revenues increased 55.3% year over year in 2Q23, giving the company a market share of 47.2%. Most recently, Cisco said its backlog is down, and in its fiscal Q1 2024 report, Robbins said the company achieved the strongest Q1 results in its history in both revenue ($14.7 billion) and profitability ($4.5 billion). "After customers implement large amounts of recently shipped product, we expect to see product order growth rates accelerate in the second half of the year," Robbins stated.

    Power moves: Aside from the Splunk splash, Cisco has acquired four other companies focused on security: Armorblox, a threat detection platform; Oort, which does identity management; and Valtix and Lightspin, both in cloud security.

    By the numbers: $28 billion. The purchase price for Splunk.

    Outlook: Cisco recently released a new security service edge (SSE) offering, a new service designed to protect multicloud workloads and a new high-end firewall. But the focus is on AI. Robbins said: "The acceleration of AI will fundamentally change our world and create new growth drivers for us. Cisco's ASIC design and scalable fabric for AI position us very well to build out the infrastructure that hyperscalers and others need to build AI ML clusters. We expect Ethernet will lead in connecting AI workloads over the next five years."

    Why they're here: The $61 billion purchase of VMware, finalized on Nov. 22, catapults Broadcom into the top echelon of networking power players. The company has cobbled together an impressive lineup of products and services, including semiconductors, storage infrastructure, networking (Brocade), network management (CA) and security (Symantec.) The goal of the VMware deal is to provide enterprises with a way to extend on-prem virtualized workloads to multi-cloud environments.

    Power moves: Broadcom bought ConnectALL to expand its value stream management (VSM) capabilities. Research firm IDC reports that VSM has become a high priority investment area for enterprises because it helps companies assess the value generated by software development initiatives.

    By the numbers: $2 billion. Seeking to reassure VMware customers anxious about what will happen after the acquisition, Broadcom CEO Hock Tan pledged that the company will spend $2 billion a year to accelerate research and development for VMware products and services.

    Outlook: Tan has outlined a clear strategy for Broadcom going forward. He said: "We will invest in extending VMware's software stack to run and manage workloads across private and public clouds, which means any enterprise can run application workloads easily, securely and seamlessly on-prem, or in any cloud platform they prefer." The increased investment will also be focused on building VMware's professional services. Gaining acquisition approval from regulators in China was a significant hurdle for Broadcom to clear; now it needs to absorb VMware without losing customers to competitors that are eagerly offering VMware migration assistance.

    3. Arista: Hitting on Ullal cylinders

    Why they're here: Arista is a powerhouse in high-performance networking aimed at the most demanding data center and cloud environments. Gartner said Arista is a visionary in wired and wireless infrastructure with its leaf and spine switches, wireless access points, and CloudVision management platform, which provides network automation, integrated security and AI/ML capabilities. Ethernet switch revenue skyrocketed 42.6% year over year, according to IDC's latest tracker, giving the company a 10.4% market share. Third-quarter revenue hit $1.5 billion, up 28% from the third quarter of 2022.

    Power moves: Arista recently announced its first foray into the WAN with a product called WAN Routing Systems that is expected to compete in the SD-WAN market. Specific components include hardware routers, virtual and cloud routers, and a WAN management service. Arista has also partnered with Equinix to deploy the WAN routing system in Equinix data centers.

    By the numbers: 75 million. Number of cumulative cloud networking ports sold.

    Outlook: Similar to Cisco, Arista envisions Ethernet becoming the network standard for AI. The company is one of the founders of the Ultra Ethernet Alliance. Arista President and CEO Jayshree Ullal said: "Generative AI Applications are pushing the envelope of networking scale akin to using all highway lanes simultaneously and efficiently. Once again, Ethernet will ultimately emerge as the winner in networking for AI. Together with IP, Ethernet will drive numerous use cases for AI training and inference. Scalable and efficient mechanisms implemented with packet spraying, flexible ordering and modern congestion control algorithms will be infused into AI-based Ethernet and IP networks. Welcome to the new decade of AI networking."

    4. Palo Alto Networks: Seeking SOC transformation

    Why they're here: Palo Alto Networks, a longtime power player in next-generation firewalls, has built out an integrated on-prem and cloud security platform. Palo Also is a leader in SD-WAN, SSE and single-vendor SASE, according to Gartner. And the company has an AI play, its extended security intelligence and automation management offering called XSIAM, which is designed to replace traditional SIEM and related point products with a more integrated, automated solution. Palo Alto is also focused on extending security to the software development process with the goal of building security into the full application lifecycle.

    Power moves: Palo Alto bought Cider Security, a leader in application security and supply chain security.

    By the numbers: $1.9 billion. Palo Alto reported fiscal first-quarter 2024 revenue grew 20% year over year to hit $1.9 billion.

    Outlook: CNBC's Jim Cramer recently described Palo Alto as "just kind of unstoppable." Fiscal year 2023 revenue grew 25% to $6.9 billion, and the company is predicting revenue growth in the 16-19% range going forward. "We finished off the year with strong execution and the changing environment drove more customers towards platformization," said Nikesh Arora, chairman and CEO of Palo Alto Networks. "Our strategy is resonating with a growing number of our customers, driving continued consolidation, to deliver superior security outcomes. We were delighted with the reception in the market for our AI-based security automation platform, XSIAM." Palo Alto doesn't just want to offer incremental improvements to enterprise security; the company talks about transformational change through offerings like Cortex XSIAM, which is designed to fundamentally change how security operations centers (SOC) operate. The goal is to embed automation and analytics to reduce manual tasks and create an AI-driven, mostly autonomous SOC.

    5. HPE (Aruba): Leaning heavily into AI

    Why they're here: AI is at the forefront of HPE's efforts, whether that's building AIOps functionality into Aruba Central, its wired and wireless network management platform, or adding large language model (LLM) offerings to GreenLake, HPE's consumption-based service for edge, on-prem and hybrid cloud computing. HPE (Aruba) is a leader in Gartner's Magic Quadrant for SD-WAN and also a leader in Gartner's Magic Quadrant for wired and wireless infrastructure, with its CX switches and Wi-Fi 6/6e access points.

    Power moves: HPE bought a slew of companies, including OpsRamp, an IT operations management company; Athonet, a leader in private 5G cellular networking; Pachyderm, whose software automates machine learning pipelines for large-scale AI applications; TidalScale, whose technology creates software-defined servers; and Axis Security, which provides an SSE platform.

    By the numbers: $1 billion. The annualized run rate for GreenLake.

    Outlook: HPE continues to chart its own path when it comes to generative AI, giving enterprises an alternative to building out AI functionality themselves, or going with a hyperscaler. The company recently announced HPE GreenLake for Large Language Models, which enables enterprises to train, tune, and deploy large-scale AI on a supercomputing platform that combines HPE's AI software and hardware. The platform includes an LLM called Luminous from German startup Aleph Alpha running on HPE Cray supercomputers in colocation facilities. HPE plans to launch AI-based applications in healthcare and life sciences, financial services, manufacturing and transportation. Said CEO Antonio Neri: "We have reached a generational market shift in AI that will be as transformational as the web, mobile and cloud. HPE is making AI, once the domain of well-funded government labs and the global cloud giants, accessible to all."

    6. Fortinet: AI-powered networking and security

    Why they're here: Sitting at the convergence of networking and security, Fortinet has generally followed the approach of building out its own product line, so the "Forti" brand of products and services is fully integrated from the jump. Gartner calls Fortinet a visionary in wired and wireless LANs. "Its FortiAP and FortiSwitch products are broadly focused on tight integration with network security capabilities leveraging its FortiGate security appliances and FortiCloud and FortiLAN cloud-based management platforms." Fortinet is also leader in Gartner's Magic Quadrant for SD-WAN. Most recently, the company unveiled Fortinet Advisor, an AI-based assistant aimed at helping security operations teams make more informed decisions, respond to threats faster, and simplify routine and complex tasks.

    Power moves: Teamed up with Google to expand its SASE points of presence (PoP) across Google Cloud's global network edge locations.

    By the numbers: 31,000. The estimated number of Fortinet's SD-WAN enterprise customers.

    Outlook: In its latest reporting period, Fortinet's quarterly revenue increased 16% year-over-year to $1.3 billion, and its service revenue, in particular, rose 28%. The company continues to bolster its product portfolio. It recently announced that FortiSASE, the company's secure access service edge offering, is now integrated with its wireless LAN portfolio with the goal of providing more options for remote workers and distributed edges to connect securely. John Maddison, chief marketing officer and executive vice president of product strategy, said: "We are the only vendor offering fully converged wired and wireless networking and AI-powered security through a single platform, providing visibility and security from the moment a user or device connects to the network.

    7. Juniper: Mist opportunities

    Why they're here: Juniper has been ahead of the curve when it comes to AI. Juniper bought Mist Systems in 2019 and has been integrating its AI capabilities throughout the Juniper portfolio of routers, switches, wireless access points, firewalls, networking software and cloud-based management systems. Gartner gives Juniper high marks for AI-driven automation, particularly its Marvis virtual network assistant. Juniper said that its AI-driven enterprise revenue is growing 17% year over the year, led by Mist AI, which grew more than 60% year over year. However, Juniper is also facing headwinds; its service provider and cloud revenues have been lagging. And according to IDC, Juniper's router revenue only increased by 2.5% year over year in the second quarter, giving it a 10.3% market share. And while its Ethernet switch revenue grew 35.2% year over year, that didn't move the needle much - Juniper's market share remains below 3%.

    Power moves: Juniper announced a $59 million restructuring plan aimed at putting more emphasis on its enterprise networking business, which has been growing faster than service provider or cloud segments.

    By the numbers: $433 million. The first quarter of 2023 marked the first time in Juniper's history that its enterprise networking business was the largest of its three core divisions, growing at 18% to reach $433 million.

    Outlook: Juniper continues to lead the way in AI-based networking. It recently announced the integration of the ChatGPT AI-based LLM with the Marvis VNA. It has added AI-based predictive threat support to its new family of firewalls. Juniper CEO Rami Rahim said: "AI networking represents a once-in-a-generation inflection point that will present us with complex technical challenges for years to come. And I believe we have the pieces at Juniper to enable this future."

    8. Extreme Networks: Extremely focused on integration

    Why they're here: Extreme's One Network approach combines wired and wireless networking, plus management software for on-prem and cloud. Gartner said Extreme's strengths are network fabric automation, digital twin capabilities and multivendor integration with Extreme Cloud, its management platform. Extreme is also a leader in AIOps capabilities, which brings the power of AI to help optimize IT operations. The company's fiscal-year 2023 earnings report reflects the strong momentum that Extreme has built: revenue was up 18% for the full year to reach $1.3 billion. In Q1 2024, revenue hit $353 million, up 19% year-over-year.

    Power moves: Extreme CEO Ed Meyercord hasn't been shy about publicly calling out Cisco. He boldly said that Extreme offers a fully integrated alternative to Cisco's multiple product lines.

    By the numbers: 650. Number of new employees Extreme hired over the past year, many from competing network vendors.

    Outlook: Rosenblatt Securities analyst Mike Genovese said: "We think there is fatigue with Cisco's products in the market, and Extreme's solutions are strong enough to compare favorably to Juniper's." Meyercord is also bullish on the future: "We outperformed our original top-line outlook for fiscal 2023, and based on industry analysts, estimates outgrew the market by two times. This, combined with the increase in volume of larger deals and new logos, is a clear indication that we're taking share from our largest competitors." He adds, "Our AIOps solutions are getting traction with customers as they look for new ways to leverage the network to drive better business outcomes."

    9. Dell: Bringing AI to on-prem environments

    Why they're here: With its powerful portfolio of high-performance computers, storage systems and networking, Dell is perfectly positioned to provide enterprises with a full-stack, on-prem, AI solution. Toward that end, Dell has teamed up with Nvidia to launch Project Helix, designed to help enterprises build and manage generative AI models on-premises. The offering combines Nvidia GPUs, LLM, software and networking with Dell PowerEdge servers and object storage systems. To make generative AI even more accessible to enterprises, Dell is offering preconfigured and pre-tested designs tailored to specific use cases. Project Helix meshes nicely with Dell's Apex as-a-service consumption pricing model, so enterprises can take advantage of generative AI without the upfront capital expenditures.

    Power moves: Bought Moogsoft for its AIOps platform that helps companies troubleshoot technical issues in their infrastructure.

    By the numbers: $100 million. The amount Dell paid to acquire Cloudify Ltd, whose technology will help Dell enhance its edge computing offerings. 

    Outlook: Dell positions itself an attractive option for enterprises that want to reduce the complexity associated with a multicloud environment. Dell is teaming up with Microsoft on Dell Apex Cloud Platform for Microsoft Azure, an offering that provides a jointly engineered on-prem appliance. Said Dell's Caitlin Gordon: "The whole magic of this is that we have integrated the full stack from the firmware all the way up to the Microsoft software, and that's fully automated." Dell is also planning to deliver Apex Cloud Platforms for VMware and Red Hat OpenShift.

    10. Nvidia: Data center dominance

    Why they're here: Gaming chip maker Nvidia bet on AI and the company's foresight, planning and execution have paid huge dividends. The company built out a full-stack AI offering that includes its own GPUs, LLM, CUDA AI software, plus networking and switch technology from its acquisition of Mellanox. Hyperscalers are snapping up Nvidia GPUs for their own data centers and Nvidia has teamed up with Dell to offer enterprises an on-prem AI platform.

    Power moves: Announced its DGX cloud service, running now on the Oracle cloud and expected to be available soon on Microsoft Azure and Google Cloud. DGX Cloud is a hardware and software package that enables enterprises to create generative AI models using Nvidia technology inside the hyperscaler's environment,

    By the numbers: $14.5 billion. Nvidia's data center revenue hit $14.5 billion in its latest quarter. Data center revenue is now 80% of the company's total revenue.

    Outlook: Nvidia continues to look for ways to spread its AI technology to new markets. It is working with ServiceNow and Accenture on a platform to enable enterprises to build custom AI apps. It has an AI platform for digital twin and robotics technologies. And Nvidia is building specialized chips for the automotive industry. Alexander Harrowell, principal analyst at Omdia, said: "There are plenty of companies that have a powerful neural-network accelerator chip, but there is only one that has Nvidia's software ecosystem." Forrester analyst Glenn O'Donnell said: "There's really no stopping this juggernaut. They will continue to dominate."






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