From ITSM to AI-driven workflows - the evolution of Jira and Atlassian's AI strategy

Jira first launched in 2002 as a simple bug-tracking and project management tool for teams, but over the years, it has evolved into a powerful IT service management (ITSM) platform. Now, Atlassian is taking the next leap by integrating AI-driven automation, predictive insights, and advanced analytics into Jira Service Management (JSM). This change marks a shift from reactive IT support to proactive service management. According to Atlassian's State of AI in Service Management report, 88% of organizations are already using AI for service management, with 89% planning to increase their investments over the next 12 months. The focus is now on tangible use and return on investment -- AI should deliver value immediately rather than requiring months or years of setup. The release of Jira Service Management aims to do just that, embedding intelligence into ITSM workflows to reduce complexity, improve response times, and provide employees with a better user experience. I spoke with Shamik Sharma, Head of Product, IT Solutions at Atlassian, to explore how AI and agentic technologies are reshaping enterprise service management -- and what this means for organizations striving to balance automation with human oversight. Sharma observed that in the last six years, Jira requirements have evolved to support additional capabilities such as asset management, tools for managing the number of laptops, monitors, projectors, rooms that IT staff have to manage and track. More recently, IT Service Management has expanded beyond just IT, because Help Desk requirements also are faced by HR teams, legal teams, or facilities teams as Sharma explained: Employees might come in and say, 'I want to make sure that my health insurance is updated, or I want to add this person to my health insurance'. And these kinds of help tickets instead of going to IT, now get routed to the HR help desk to solve. So it's kind of gone through this transition from service desk, to operations, to asset management, and all of these capabilities have now started morphing from IT Service Management into enterprise service management. With AI, Atlassian is accelerating this transformation, integrating machine learning models to improve ticket routing, automate responses, and generate insights that support faster decision-making. Sharma highlighted that AI-driven features in Jira are not just about automation but also about enhancing collaboration and knowledge sharing: Our AI capabilities in Jira Service Management are built on years of understanding how teams work. The system learns from historical interactions, recognizes patterns, and suggests solutions -- reducing the need for redundant troubleshooting and improving resolution accuracy. This dovetails with existing tools in Atlassian's product suite - Confluence has been used for years as an effective knowledge base for enterprises across a broad range of industries. Atlassian's latest AI advancements enable proactive incident management by surfacing relevant past incidents, priority levels, change risks, and even suggesting the best responders. Embedded into this transformation are Rovo Agents -- AI-powered virtual teammates that assist with root cause analysis, surface relevant third-party data, and recommend actions to IT teams. During an incident, Rovo agents help teams ask the right questions, generate post-incident reports, and automate key response workflows. This aims to help IT teams resolve issues faster - and cut down the amount of manual work while ensuring the important things like documentation don't get neglected. Virtual service agents are embedded into platforms like Slack, Teams, email, and web widgets, ensuring employees receive immediate support wherever they work. The service agents are now capable of supporting all major languages, so if, for example, a library and IT helpdesk is switched over from a personal service during the day time to a different region at night, ongoing support can be provided 24/7. According to Atlassian, customers report that these AI agents handle up to 75% of internal requests -- many of which can be repetitive, e.g. Wi-Fi issues -- significantly improving productivity and employee satisfaction. We discussed the AI-powered HR capabilities in a little more depth, including automated onboarding workflows, AI-generated request types, and deeper integrations with HR platforms like Workday and Okta. These enhancements simplify common HR processes, such as provisioning new employee equipment or processing exit interviews. I asked Sharma about data privacy, noting that AI isn't an all-encompassing tool for every question. He elaborated: We provide a lot of capabilities across the board, allowing people to be informed of the source of the information, and whether the source is a primary source, or it's a secondary derived source where AI has summarized it, or AI has created the answer based on the knowledge it has. When you're deploying it, the administrator can configure what kind of answers can be answered by AI, and what kind of answers, triggers and areas of responsibility should go to a human agent, including which aspects the human agent can themselves be helped by AI or not. All of these rules about when can you actually involve AI can be configured by the admin. We also provide reports and analytics about where people used AI and where they didn't. And then the administrators can choose topic areas that they don't want to use an AI agent, for example payroll. They can completely disable AI answers as well as AI help providers for those topics. We provide all of those controls. And that, I think, is one of the big reasons why our customers are getting more comfortable with adoption because we're providing them with full privacy controls. Sharma and I agreed during our conversation that one of the most overlooked aspects of AI adoption is change management. Even with robust AI capabilities, enterprises need to ensure that teams are ready to embrace these new technologies and workflows. Sharma pointed out that successful AI integration requires proactive change management strategies: Adoption is a journey. Enterprises that invest in structured change management programs -- training, stakeholder engagement, and phased rollouts -- see far better results than those that expect employees to adapt overnight. We've seen that the best results come when organizations introduce AI in iterative steps, showing clear value at each stage. Atlassian has built support structures into its service management to help enterprises navigate this transition. Features such as AI-driven training recommendations, guided onboarding, and transparent AI decision logs help ensure teams understand and trust the technology they are using. Another challenge that companies face with AI adoption is the risk of vendor lock-in. Atlassian aims to mitigate this by ensuring its platform integrates seamlessly with third-party tools and existing ITSM stacks. Sharma explained: Our goal isn't to create a walled garden -- it's to build an open ecosystem where AI-powered automation can work across platforms. Whether you're using Slack, Teams, or third-party ITSM solutions, Atlassian AI is designed to interoperate and enhance existing workflows. This extensibility also extends to Atlassian's broader product suite, with AI capabilities weaving into Confluence, Jira Software, and Bitbucket to create a more connected enterprise service experience. For IT leaders justifying AI investments, return on investment and real-world use cases are essential to making the case for change. Sharma pointed to tangible business outcomes that Atlassian customers are already experiencing. Companies using AI-driven service management have reported up to a 50% reduction in resolution times and significant cost savings in IT support. AI doesn't just optimize processes -- it fundamentally changes how teams work, reducing friction and boosting productivity. A recent economic impact study commissioned by Atlassian found that: Atlassian's latest announcement is far from just an ITSM play -- it's a broader vision for how AI can enhance enterprise workflows across IT, HR, and many other divisions across different organizations. The success of AI-driven service management depends not only on technology but also on an organization's readiness to adapt and integrate AI thoughtfully into its operations. Sharma believes that AI's evolution in enterprise service management will be shaped by three key trends: the increasing use of generative AI for knowledge management, deeper automation in workflow orchestration, and a growing emphasis on ethical AI practices to ensure fairness and transparency in decision-making. He noted that it's not a matter of whether AI will be integrated, but how effectively enterprises can implement it to see tangible value. With Atlassian's focus on openness, adaptability, and responsible AI deployment, its role in shaping the future of service management is one to watch. We'll be on the ground in Anaheim at Atlassian's Team '25 event in April, looking for use cases.

diginomica

Wed, 19 Feb, 6:54 PM UTC

How Jotform AI Agents Improve Customer Service and Boost Efficiency

Are you searching for a way to improve customer interactions while automating repetitive tasks in your business? Jotform AI agents provide a powerful, user-friendly solution to help you achieve these objectives. These AI-powered tools enable you to create, customize, and deploy virtual assistants tailored to your specific needs. Whether your focus is on customer service, sales, or human resources, Jotform AI agents integrate seamlessly across platforms, offering a versatile and efficient approach to optimizing your operations. By using these tools, businesses can enhance productivity and maintain a professional brand presence. Whether you're running a small online store or managing a large-scale enterprise, Jotform AI agents offer a flexible, user-friendly solution to meet your needs. From creating customized virtual assistants that handle FAQs to integrating them across platforms like WhatsApp or your website, these agents are built to work for you. And the best part? You don't need to be a tech wizard to get started. This guide by Corbin Brown walks you through everything you need to know, from setting up your first AI agent to unlocking its advanced features, so you can focus on what matters most -- growing your business. Jotform simplifies the process of building AI agents, even for those with no prior experience. The platform offers pre-built templates designed for various industries, allowing you to get started quickly and efficiently. Follow these steps to create your AI agent: This step-by-step process gives you full control over your agent's design and behavior, making sure it aligns perfectly with your operational goals. One of the most valuable features of Jotform AI agents is their ability to integrate effortlessly across multiple platforms. This flexibility allows your business to connect with customers wherever they are, making sure a consistent and accessible experience. Key integration options include: These integration capabilities ensure your AI agent remains a reliable and effective tool for engaging with your audience across different platforms. Dive deeper into AI Agents with other articles and guides we have written below. Jotform agents are designed with extensive customization options, allowing you to create a virtual assistant that aligns with your brand identity and communication style. You can personalize several key elements, including: This level of customization ensures your AI agent not only looks professional but also communicates effectively with your audience, enhancing user satisfaction. To ensure your AI agent delivers accurate and helpful responses, it's essential to train it using your business's knowledge base. This process involves equipping the agent with relevant and up-to-date information. Here's how you can do it: By providing your agent with the right data, you can ensure it remains a reliable and valuable resource for your customers. Jotform AI agents are equipped with advanced automation features that go beyond basic question-and-answer interactions. These capabilities can significantly reduce manual workloads and improve operational efficiency. Key features include: These advanced features make Jotform AI agents a powerful tool for automating complex workflows and enhancing productivity. To maximize the effectiveness of your agent, Jotform provides robust monitoring and analytics tools. These tools allow you to track performance and make data-driven improvements over time. Key functionalities include: This focus on continuous improvement ensures your AI agent remains a valuable asset as your business grows and adapts to new challenges. Jotform AI agents are versatile tools with applications across a wide range of industries. Here are some examples of how they can be used effectively: The platform's intuitive design ensures that even users with minimal technical expertise can create and deploy effective AI agents, making it accessible to businesses of all sizes and industries.

Geeky Gadgets

Fri, 28 Feb, 10:13 AM UTC

Atlassian Team '25 - how Valiantys helps Atlassian customers modernize, from platform to process

Before the main keynote kicks off at Atlassian Team '25 in Anaheim, conversations on the ground are already pointing to one dominant theme - how to turn the promise of AI into real, measurable change. Among the voices shaping that conversation is Conner McNeil, Head of Platform Development at Valiantys. In a sit-down ahead of the event's headline announcements, McNeil shares how Valiantys is helping enterprise customers not only adopt new AI tools, but also rethink the processes that determine whether those tools actually deliver results. Valiantys is a long-time Atlassian partner that helps large companies modernize the way they work -- especially those dealing with outdated systems and complex tech setups. As McNeil puts it: My role really boils down to helping our largest customers with the most complex footprints adopt cloud tools and make a platform transformation. For Valiantys, conversations about AI always start with understanding the customer's actual challenges. Many organizations come to them after realizing their existing systems are slowing them down. "Their systems are old, their tools don't talk to each other, and they're trying to figure out where to even begin," McNeil explains. At that point, AI often enters the conversation -- but it can bring confusion rather than clarity. There's a lot of hype in the market, and most companies aren't sure how to move from flashy demos to real results. McNeil notes: It's really hard for a customer to look past the hype and say, 'Okay, how do I actually use this?' One of the most common pitfalls he sees is companies investing in new technologies without improving the underlying processes. He remarks: If you have bad processes, what you do is enable a customer to do bad processes faster. You miss a huge opportunity. Instead, Valiantys starts by looking at how the organization works -- its structure, goals, industry, and teams -- and then builds a roadmap for improvement. From there, they layer in the right technology, including AI, but only where it truly fits. For McNeil, the key to successful transformation isn't just technical expertise -- it's trust. He observes: If your intention is anything other than to be a trusted advisor... you're doing something wrong. That philosophy shapes Valiantys' work across industries like automotive, retail, and software. Regardless of the customer's size or sector, the team looks for ways to connect systems, simplify workflows, and reduce wasted effort. McNeil refers to the System of Work - a key tenet of Atlassian's philosophy: We think of 'System of Work' as providing something that actually works across the business. So people can stop jumping between disconnected tools and just focus. Much of Valiantys' current AI work centers around Rovo, Atlassian's new AI platform. McNeil observed that it took time with customers to show them the full extent of Rovo's capabilities. This is done with the help of Forge, Atlassian's cloud development platform. Forge lets developers build custom workflows, automations, and AI agents directly inside Jira and Confluence -- without having to manage infrastructure. "Customers didn't realize you could already build custom AI agents through Forge," McNeil points out. By combining Rovo with Forge, Valiantys has built agents that search across systems, pull together data, write documentation, and even make updates to external platforms -- all automatically. To help customers turn AI from a concept into a business case, Valiantys created its AI ROI Discovery program. The approach is simple: spend time with the customer, learn how they work, and identify where AI could make a measurable impact. McNeil explains: It's not about saying, 'These tools are cool,' it's about saying, 'Here's how much time and money you could save -- and here's the proof.' That message resonates especially well with large enterprises. In organizations with 60,000 or more users, even small gains add up fast. "You're talking eight figures in savings just by removing manual work," McNeil estimates. In nearly every industry, organizations want better ways to search across scattered knowledge bases and get quick, accurate answers. Valiantys has been in the Atlassian ecosystem for nearly two decades -- and that experience shapes how it guides companies through change. "We've done hundreds of cloud migrations and platform implementations," McNeil shares. "We're able to say to customers, 'We've seen this before -- here's what works.'" That history also allows Valiantys to collaborate closely with Atlassian itself. He says: We're on the ground with customers, and AI is just part of our business in solving problems and how we support our customers across the board. We have some great relationships with the team that's building Rovo at Atlassian, and we've been able to give a lot of feedback, be part of early-access programs, and build some tooling together with them. It's a great partnership because they're building a really good product, and so we get to see our customers benefit from that. In the meantime, Valiantys is expanding its capabilities rapidly. That expansion includes boot camps to train teams on Forge, co-developing custom workflows, and launching broader consulting engagements that help enterprises modernize at scale. Whether it's developing intelligent workflows or building tailored automations, Valiantys is helping organizations make real changes with Atlassian. As Atlassian Team '25 kicks off, it's clear that AI isn't aspirational - it's operational. Over the next two days, we'll be speaking with Atlassian executives and customers to dig deeper into the thinking behind the platform's latest developments -- and to find out how those decisions are landing with knowledge workers.

diginomica

Wed, 9 Apr, 10:16 AM UTC

Atlassian Team '25 - customers share first impressions of putting the Rovo AI agent to work

Atlassian's AI agent Rovo generated a lot of buzz at this week's Team '25 conference. Rolled out six months ago, it has had an enthusiastic welcome from customers, some of whom were already happy to talk about their experiences and offer advice and encouragement to others. In a shared session, David Todd, Director of IT & DEX at 1E, recently acquired by TeamViewer, talked about how agents have reduced ticket handling times by as much as 80%, and automated some big, tedious jobs. Meanwhile Frederick Frenzel, Director of PMO at HarperCollins Publishers, discussed how the global publishing house was using agents to manage project requests, streamline processes and reduce backlogs. 1E provides system management tools to support what it calls the Digital Employee Experience (DEX). It was acquired by remote connectivity vendor TeamViewer at the end of last year. David Todd says he first saw Rovo at the Team '24 Europe event last October, and immediately saw how it could benefit his team. He goes on: We use Atlassian across our business, and fully embrace the System of Work approach. I think that's really helped us as we get the most benefit out of our Rovo agents when we have so much data in that system of work available to us. He saw the use case for it, and after a quick demo at the show he could fully understand how easy it would be to adopt and really get the value out of it. He comments: I didn't want this to be a top down strategy, because that doesn't work. I don't understand everyone's business processes. So one of the first things we did was [set up] some Centers of Excellence for Atlassian, bringing people from other departments like HR, marketing, and finance to help us out. Todd held sessions for the entire company to join and ask questions. One key request was about getting Rovo agents to write code. The company's Tachyon product has its own client endpoint management language called Scale. Todd says that although this isn't difficult to learn, you still have to know how to write it -- so could Rovo learn it? He goes on: Whilst the meeting carried on, we did it, and we connected [Rovo] to guidance for where we showed customers how to write Scale. I said, create me an agent that is an expert in writing scale. I want you to explain how it's written, and put comments in the documentation you created, and that was pretty much it. And we did that during the call and demonstrated straight away. He said that people were coming up with ideas on how to start to use it, and then they took that away to their teams, and started to discuss their processes and how they can improve, championing it from within. 1E now uses Rovo agents, not just to resolve support tickets, but also to prevent support tickets even coming in by automating knowledge base article creation, and then providing solutions to the customer. Todd explains: AI is brilliant, and it's not a replacement for people. It enhances what we can do and also takes away the things that we don't want to do. Writing knowledge based articles is boring. It's not helping the customers directly. I want our service desk agents to be helping customers directly. The huge change is freeing these guys up to do what they can do. Frederick Frenzel says the AI agent has already had a similar effect at HarperCollins, bringing significant productivity increases to the Project Management Office. But it was important to set up the right guardrails. He comments: At the end of it we're a regular media organization. So when we look at a tool like Rovo it's a really big concern of ours to make sure that we're looking out for our content providers and making sure everything's secure, and the right access is in the right spot. In early access to Rovo, the company went into test mode, building up use cases, starting from the project management team. He explains: That's everything from taking our handwritten notes and starting small, and trying to take all those kinds of mundane, tedious tasks out the way. Before the Rovo agents were adopted it took weeks of planning, and getting a lot of people to come together, to lead and move things forward. Frenzel continues: Our Day-to-day Demand to Deliver (DDD) is everything from the business intake, which in our business is our customer, just like our content providers have the customers that buy the books. When we have that initial entry point, we're using JIRA Service Management to bring in our intake of requests. So it's an internal customer bringing that in, and it went through a series of classic project management steps. Leadership is approving those requests at the secondary step to make sure they can fit within the goals of the organization. The volume of requests was an issue, as he explains: So we worked with Atlassian to focus. They worked with us to ensure that when we looked at this design solution, we really focused on the key aspects, and found what the biggest blocks were. Our scale was there, but it was just that. There were too many requests at the end of the day. Frenzel has already deployed a few custom agents to help out various processes, which he says are making a big difference. He gives the example of the first ticket submission recap agent. When the business submits a request, the agent evaluates it and pulls together what that business person is trying to achieve, thus streamlining the process. Using agents for prioritizing backlogs has been one of the biggest wins. He explains: We have to make sure our goals are aligned. The weekly recap ticket agent was able to look at all those requests and prioritize them in a particular order. We were able to choose. edit and 'thumbs up, thumbs down' where needed, and it tied to the goals that we set for the organization... "I remember an entire backlog when I was doing the cleanup. It was 50 requests that were under evaluation that we had to do and get to discovery. I ran the agent, and it would have taken hours for someone to do single artifacts for each one. It brought in all 50 of them in 15 minutes. Both Frenzel and Todd are enthusiastic about the impact Rovo has had both on their processes and on collaboration. However they emphasize that it is critical to involve multiple teams and business leaders when beginning to implement AI agents. Todd concludes:

diginomica

Fri, 11 Apr, 7:00 PM UTC

Easily Automate Your Shopify Customer Service wWith AI (No Coding)

Imagine this: a customer visits your Shopify store at midnight, eager to track their order or inquire about a product. With no one available to respond, they leave frustrated, possibly never to return. Now, picture an alternative scenario where an intelligent chatbot instantly answers their questions, provides personalized recommendations, and even escalates complex issues to your team -- all without requiring a single line of code. Sounds fantastic, right? That's the promise of automating Shopify customer service with AI. By using tools like the Jotform AI chatbot, you can deliver round-the-clock support and seamless customer experiences, all while freeing up your team to focus on high-value tasks. Kevin Stratvert explains how you can integrate an AI chatbot into your Shopify store effortlessly, even if you have zero technical expertise. You'll discover how automation can handle repetitive inquiries, sync with your store's data, and even reflect your brand's unique personality through customization. Whether you're looking to reduce response times, scale your operations, or simply improve customer satisfaction, this no-code solution offers a practical path forward. Ready to uncover how AI can transform your Shopify store's customer service? Let's reimagine what's possible in e-commerce support. E-commerce businesses frequently face repetitive customer inquiries, such as questions about order tracking, product availability, or return policies. Addressing these manually can overwhelm your support team, leading to slower response times and reduced efficiency. Automating these tasks with an AI chatbot offers several advantages: This scalable solution ensures your business can handle increasing customer demands without compromising service quality, making it an essential tool for growth. Setting up an AI chatbot for your Shopify store is straightforward and requires no technical expertise. To begin, you'll need an active Shopify store and access to the Jotform AI chatbot app. The integration process is simple: Once installed, the chatbot is ready to assist customers by providing accurate and relevant information based on your store's data. The Jotform AI chatbot is designed to enhance customer service and streamline your store's operations. Its key features include: These features ensure that your customers receive timely, accurate, and personalized support, enhancing their overall shopping experience. One of the standout aspects of the Jotform AI chatbot is its flexibility and adaptability. You can customize its appearance and functionality to reflect your brand identity, making sure a seamless integration with your store. Customization options include: The chatbot also learns from your store's data, automatically syncing with your inventory, collections, and campaigns to stay up-to-date. Additionally, you can manually train the chatbot by adding custom knowledge, such as Q&A pairs or links, making sure it remains accurate and relevant as your business evolves. To ensure the chatbot delivers optimal results, it's important to monitor its performance regularly. The platform provides analytics on customer interactions, allowing you to identify areas for improvement. Based on these insights, you can refine the chatbot's training and responses to better meet customer expectations. For businesses of all sizes, scalability is a key consideration. Jotform offers a free starter plan, which includes a limited number of monthly conversations and voice call minutes. As your store grows, you can upgrade to paid plans for higher usage limits and additional features. This flexibility makes the chatbot a cost-effective solution, whether you're running a small startup or managing a large enterprise. Integrating an AI chatbot into your Shopify store provides numerous benefits that can transform your customer service operations: By using AI-powered customer service, you can enhance customer satisfaction, streamline operations, and position your business for long-term success. Whether you're just starting out or managing a growing e-commerce store, an AI chatbot is a practical and powerful tool to help you achieve your goals efficiently.

Geeky Gadgets

Wed, 13 Aug, 8:09 AM UTC

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