1. As AI continues to evolve, how do you adjust AI strategy in real time to ensure it meets the changing needs of both the market and your customers?
Since the start of the AI revolution, SaaS companies — and beyond — have introduced numerous AI-powered solutions to stay relevant and competitive. While some of these products meet expectations and are in use today, there is an opportunity to address ongoing customer needs to minimize pain points.
At Appfire, we understand that innovation is critical to remain at the forefront of our industry. We actively monitor the industry for best practices and stay up-to-date with market trends. While our approach to AI integration has been more gradual, it has been strategic. We’re focused on ensuring the “AI readiness” of each product, versus introducing multiple applications without certainty that they’ll address the pain points of our customers.
Appfire’s designers and product managers routinely connect with our customers to gain insight on their needs. Our dedicated user research group manages broader research initiatives which are leveraged for our product roadmaps. With this approach, we’re empowered to develop AI-powered applications that can fill the gaps and drive almost immediate value for our customers.
2. How do you balance the development of new AI-driven apps and the enhancement of existing products to create a comprehensive ecosystem for users?
Appfire has a broad and unique portfolio of problem-solving applications that span across four ecosystems. Naturally, our instinct is to enhance our existing apps with AI and elevate the user experience. This ensures we’re optimizing the apps we already have and allows customers to continue working with the apps that suit them versus having to find and learn new ones.
If we notice that updating an existing app with AI doesn’t make sense, we’d create a new app. For example, our recently launched WorkFlow Pro app was deployed on Atlassian’s Rovo – an AI-Powered teamwork tool for Jira and Confluence — because such functionality was not achievable in our existing apps.
3.What trends in AI development are you observing that are most likely to impact how organizations plan, track, and execute work in the coming years?
Two areas of AI development remain top of mind for many SaaS vendors, including Appfire. First, the rise of AI-powered agents and second, ensuring that enterprises’ use of AI doesn’t compromise the security of proprietary or customer data.
Agent technology has the potential to significantly improve the efficiency of knowledge workers and streamline their tasks. While some may argue current agent use cases are limited, massive investments in agentic workflows throughout the software value chains are becoming a norm, including Atlassian’s Rovo and Salesforce’s Agentforce.
As AI capabilities expand, concerns around data security and privacy risks increase alongside it. Enterprises must prioritize AI integrations that respect and protect their assets and those of their customers. For Appfire, maintaining the highest standards of data security and compliance is a top priority. Our award-winning Trust Center enables customers, partners, and prospects to access information on the security, privacy, and compliance of our products and services. Finding the balance between innovation and healthy security practices is essential to unlock AI’s full potential.
4. Can you provide examples of how your shared AI services, such as the summarization feature, are being leveraged across multiple applications to improve efficiency?
We see a future where all our apps can leverage AI and therefore sought to build a set of centralized AI services that our product teams can utilize. Our internal AI platform service enables our apps access to multiple models (both commercial and locally hosted) and to monitor and manage the usage of AI for individual apps.
Having multiple models allows our apps to select one that is most suitable to tackle the task at hand. For example, to create a customer feature that asks questions on app functionality or to self-troubleshoot, it’s best to use an existing large language model like ChatGPT. However, for an assignment that is very specific and narrow, like estimating story points, a different model might drive better results at a potentially lower cost.
5. How do you envision AI-driven apps transforming goal-setting, project planning, and data management within the ecosystem in the next few years?
AI will continue to have a profound impact on what knowledge workers can accomplish and how they interact with software. With WorkFlow Pro, we’ve differentiated ourselves by focusing on producing AI agents that can truly accelerate human work. Furthermore, Appfire is applying AI in practical, outcome-driven ways that will help users get work done faster and more efficiently.
We applied this approach to our Canned Responses app, which allows support agents to store templates of frequently used answers to customers. As the number of templates rose, it became more difficult and time consuming to sift through them, making them unmanageable. In response, we leveraged AI to create the “Smart Reply” feature which analyzes the customer email/request and finds the most appropriate template. Support agents are then offered an AI-written reply, cutting response time and easing efficiency.
In the future, “agentic workflows” will become more popular and AI agents will act more like human collaborators, capable of tackling complex tasks, gathering information from multiple sources, and coordinating with other agents and people. This agent-run approach will go beyond simple interactions like those with ChatGPT; agents will become more autonomous and proactive — perhaps even anticipating next steps. Voice interactions with agents will also become more common, allowing users to work while on the go.
Maciej Saganowski is Director of AI Products at Appfire, a leading global provider of next-generation software that enhances, augments, extends, and connects the world’s leading platforms such as Atlassian, Microsoft, monday.com and Salesforce. Maciej focuses on driving AI innovation and delivering impactful solutions for Appfire customers. He is the founder and curator of ProductCamp Poland, a knowledge-sharing conference focused on digital product design and management for product managers and designers across Europe. Prior to joining Appfire, Maciej held positions at companies including Ultimo.studio and Booksy.