Insights on adaptability, data-driven growth, and AI readiness shaping modern enterprises.
Dean, from launching your startup in 1989 to competing with giants like Microsoft and now leading a global tech enterprise—what personal philosophies have carried you through such pivotal chapters of the tech industry?
In my over 35 years navigating the space I have realized that grit alone is not enough to build a company that withstands the test of time.
Learning new ways has never been easy for me. Like most entrepreneurs, I am hardwired to overcome challenges personally, no matter how difficult they are. I am also usually single-mindedly focused on success. In the beginning, pouring passion and perseverance into Infragistics worked, we won deals with a number of major international companies, including Intuit, Morgan Stanley, Credit Suisse, Bank of America, Fidelity, Ikea, Exxon and Charles Schwab.
But of course challenges did begin to emerge – bigger challenges that I couldn’t solve by continuing the way I always had. I realized I needed to change my approach and become more strategic about running my company if I was to compete in the ever-changing market.
From then on, I’ve run with the philosophy that a company is like an organic being, endlessly needing to adapt and change. It must continually create the next version of itself, adapting at a relentless pace to survive and prosper.
At each stage of your business growth, you will have to adapt, learn, and improve your operations to grow and be profitable. Especially in the tech industry, a business won’t survive being stagnant, it needs to be agile enough to respond to the relentlessly changing marketplace. As a leader I have made it my mission to be self-reflective, transparent and in constant pursuance of an organization where learning is a primary purpose and goal.
You’ve seen the rise of the internet, endured the dot-com bust, and now stand at the edge of an AI-driven era. What patterns do you recognize from previous waves of disruption that business leaders should keep in mind today?
When a new technology emerges or a large shift hits the technology industry, many leaders do one of two extremes. Either, they dig their feet in and believe that the disruption is a passing fad and don’t change anything about their business – or they try to overhaul to match changing market demand way too quickly.
As I mentioned above, being adaptable is essential to withstanding and thriving through market ups and downs, but that does not mean completely changing your business overnight. Instead, leaders should evaluate how to shift accordingly while still staying true to their core business mission. Small changes can be implemented to start and can then gradually become more ingrained over time. It’s a strategic process that is important to begin as soon as possible without laying it all on the line right away.
As AI gains momentum, what do you see as the most transformative applications for go-to-market teams in particular?
AI has the potential to completely reshape how companies go to market. However to do so, teams need to move beyond individual tactical applications and toward a more cohesive overall company plan.
Go-to-market teams can use AI to support every part of their day to day operations from identifying ideal customers and finding market-fit to creating relevant messaging and measuring success. For example, when launching a new product, data is essential to determine the best strategy. AI can pull this data and contextualize it, in order to inform teams on what customers want, like, and expect. With this integral insight, businesses can better determine their target audience as well as any last minute changes that need to be made before release.
As AI empowers teams with this insider knowledge on their target audiences, companies will be able to work more quickly and more effectively, refining messaging, optimizing spend and growing revenue in real time.
Slingshot is your latest venture. How does it enable teams to translate data into action—and where does AI fit into that workflow?
Data is only actionable if it’s contextualized with insights from across the organization. Slingshot brings together companies’ data from multiple sources and systems in order for teams to have a holistic view of what’s working – or isn’t – and where.
By creating a cohesive place for entire organizations’ data, the work management platform has created an AI foundation for companies. Slingshot is pairing the centralized data with conversational AI to automate insights for teams, so they can quickly derive clear, actionable insights from all of a company’s data sources that track performance, process, people and profitability in seconds. These automated insights eliminate the task of manually sifting through and analyzing data, so teams can increase productivity, make decisions faster and prioritize the strategic work that drives business growth.
For example, teams can ask Slingshot AI questions like “What’s the sales forecast for Q2?” or “Are there any customer trends?” and receive answers immediately. It can also automate data visualizations to help teams identify trends, assess performance and forecast the next best steps for the business or a given project.
AI thrives on quality data. What foundational steps should businesses take today to ensure their data ecosystems are future-ready for AI integration?
Every company has some data infrastructure already in place, but most are disjointed, with data spread across multiple departments, software systems and gatekeepers. In order for AI integration to be successful it is essential for companies to break down these siloes and centralize data from across the organization into one location that’s accessible by all teams and AI.
Additionally the data in this pool needs to be top quality. To ensure this, companies need to standardize how the data is reported, remove duplicates, address any missing values and correct errors. Three main buckets to make sure are touched upon when cleaning and organizing data are the following:
Completeness: If there are certain values missing or outside of a set constraint, then the AI model may generate skewed outputs or make incorrect assumptions. Complete data will have all of the required values filled out and within a set limit or range.
Consistency: When centralizing data from different departments within a company, there’s likely to be duplicate datasets. However, if these datasets show conflicting stories, companies must first determine which data is accurate before using it for AI.
Timeliness: While historical data can be useful to understand past trends and track patterns, relying on outdated data can skew AI outputs. If a data set no longer reflects current market conditions or sentiment, then it’s likely not as useful.
There’s a lot of hype around AI tools, but few talk about organizational readiness. What’s your approach to preparing teams—culturally and operationally—for such a deep shift?
Education is integral. Even though AI has gone mainstream, there’s still uneasiness around it–especially when it comes to people’s jobs.
When many people hear AI they instantly think about how it will affect their jobs. And there is truth in the belief that it will change things – but not for the worse. AI has the potential to be teams’ go to collaborator, they just need to first understand how to properly lean on it for better results.
Before anything else it’s important to transparently speak with employees on the set objectives you are hoping to achieve with the integration of an AI tool. Discuss how it will be used as well as what it will be used for. For example, leaders can make clear the addition of AI is to cut out the mundane, manual tasks that employees do every day in order to give them time back to focus on more creative or strategic tasks that only they can do. With this knowledge, any concerns should be assuaged and employees will have the information they need to use AI to uplevel their work.
You emphasize innovation culture. How do you practically embed that mindset into large organizations without it becoming just another buzzword?
In my 35+ years as Founder and CEO I have learned four key ways to build a culture of innovation – and it all starts with employee ownership. When employees feel they have a personal stake in an organization and its future, they’re more invested in the company’s performance and empowered to do their best. The four main ways to engage employees in my experience are:
Continuously reinforce the company’s bigger purpose and where employees fit into it. What’s the company’s purpose? What are the company’s goals? Every employee should be able to answer these questions of their organization. Only then can they fully understand where they fit into the bigger picture and how they can contribute to the higher goal. It’s up to leaders to communicate this bigger purpose across the entire organization.
Encourage employees to manage up. One of the hardest parts about creating a culture of ownership is that ownership can’t be given — employees must be willing to step up to the plate and take it. Open communication between managers and their direct reports is essential. One-on-one meetings, whether they’re weekly or monthly, offer a place for employees to reiterate their current priorities and discuss how these support their managers’ priorities and goals.
Build a foundation of trust. Having a stake in an organization and its success comes from not only believing in the company and its purpose, but believing in the people behind it. The single most important thing for building a cohesive team and relationships in the workplace is trust. One of the most simple ways to do this is by showing emotion and connecting with others on a more personal level.
Share clear goals but allow freedom in achieving them. A clear understanding of what’s expected among teams, without dictating how it’s delivered, gives people autonomy to get work done their way and still deliver results. When employees pave their own way to achieve something, it creates more intrinsic motivation and they feel even more of an attachment to it, because they’re overseeing the entire process on their terms from start to finish.
Agentic AI is gaining traction. How do you see autonomous agents shaping enterprise productivity over the next three to five years?
AI agents will play a large role in making company’s data actionable so that they can get to market quickly and with confidence.
Agentic AI will gather and contextualize complex data so that teams have insights relevant to their day to day task at their fingertips. This will cut out hours of manual searching and analyzing, allowing teams to move at a pace previously not possible. Agents will become employees’ right hand man, acting as a true team member to drive forward goals.
With so many companies chasing AI as a competitive edge, what separates those who will sustain impact from those just checking a box?
The main thing that will separate companies from others is a data-driven strategy. With company wide insights into how your business is performing it will be abundantly clear where AI use cases will actually drive forward productivity and gains. It’s important to be strategic in how AI is implemented otherwise the process and cost will not be worth it. Those who are rushing to implementation without a strategy will not see any true impact.
Finally, looking beyond technology, what leadership traits do you believe will be most essential in steering organizations through the next decade of change?
Transparency and an open mind is essential for leaders to successfully guide their companies through any momentous shifts, whether it’s now or in ten years. As a leader myself who has years of experience under my belt, I can confidently say that I still don’t know everything. It’s essential to keep an eye on what’s emerging in the market, what’s being said by other leaders and – perhaps most importantly – what your employees are discovering. Leaders’ biggest assets are their team members. Building an organization is not a one man job. It’s a group effort. Every person in an organization has the potential to spearhead an innovation that will propel the company to new heights. Leaders just need to be open to it.
A quote or advice from the author
A company is like an organic being – endlessly needing to adapt and change. It must continually create the next version of itself, adapting at a relentless pace, to survive and prosper.
Dean Guida
Dean Guida is the 35+ year entrepreneur and CEO behind enterprise software company Infragistics. The company has operations in six countries with more than two million developers using its software, and a client roster that boasts 100% of the S&P 500, including Fidelity, Morgan Stanley, Exxon, Intuit, and Bank of America. Dean has led his business through a series of tumultuous moments, crystallizing insights he’s gathered at each key moment in his book,’When Grit Is Not Enough’.
