At Techonomy 24, Darko Tadorovic, VP of Engineering & Delivery, and Sanja Bogdanovic-Dinic, Head of Data Solution at HTEC shared transformative insights on preparing organizations for AI integration. Their panel discussion delved into the critical importance of data readiness and organizational adaptability in navigating the AI revolution.
Tadorovic began by contextualizing HTEC’s role in the industry, emphasizing their unique position as engineering service providers for a diverse client base, including Fortune 100 companies and non-tech organizations. He noted the particular challenges of assisting non-tech companies to modernize. “We created beautiful products that nobody used,” Tadorovic admitted, reflecting on early missteps. These failures underscored the necessity of involving end-users from the start and understanding the nuances of organizational culture. “It’s very important that we focus on the people who are going to use these solutions moving forward,” he emphasized.
The Essence of Data Readiness
Bogdanovic-Dinic expanded on the foundational concept of data readiness, a recurring theme in their discussion. “Data readiness is not what usually first comes to mind,” she explained. “It’s not just about being technically capable of implementing a data or AI solution. It’s about the alignment of technology, data, people, processes, and business strategy.” She highlighted that the dynamic nature of AI solutions demands a holistic approach to ensure success.
Using a maritime company as a case study, Bogdanovic-Dinic illustrated the journey from operational chaos to streamlined efficiency. “When we started, all operations were done manually, with no communication or standardization between departments,” she said. By centralizing data and processes, HTEC enabled the company to optimize voyage planning and create new revenue streams. This transformation, she pointed out, required extensive change management. “No one likes someone external to handle change management,” she admitted, but underscored that internal adaptation is key to long-term success.
Overcoming Resistance to AI Adoption
Both speakers acknowledged the human factor as the crux of AI adoption. Tadorovic recalled an oil transportation company where resistance from a single employee delayed the implementation of an AI solution. “It took us a year to persuade that person to give the solution a chance,” he shared. This experience shaped HTEC’s strategy of co-building solutions with end-users to ensure adoption. “We avoid working only with executives,” Tadorovic explained. “Instead, we focus on the people in the trenches because they have the power to make or break the implementation.”
Bogdanovic-Dinic echoed these sentiments, framing AI adoption as a cultural shift. “It’s change management that needs to happen,” she stated. “Even the most sophisticated solution will fail without adoption.” This psychological and cultural aspect of implementation, she noted, is often overlooked but is critical for success.
The Broader Implications of AI as a Platform Shift
The speakers also discussed AI’s role as a platform shift, comparable to the internet or mobile revolutions. “AI is a new platform, and we don’t fully know what it will become,” Tadorovic remarked. This uncertainty, combined with rapid technological advancements, necessitates a deep understanding of AI across all levels of an organization. “We need to invest in the knowledge of our people,” he urged. “Let them be creative, test ideas, and fail in a controlled environment.”
Bogdanovic-Dinic stressed that this democratization of AI knowledge is essential as AI becomes integrated into all organizational functions. “There’s a translation layer being removed,” she said. “It’s no longer just the CIO or IT department; marketing teams and entry-level staff will interact directly with massive databases.”
Building the Intelligent Enterprise
Ultimately, the speakers emphasized that building the intelligent enterprise requires more than just technical prowess. It demands a cultural and organizational shift, underpinned by robust change management and a commitment to ongoing education. As Tadorovic aptly summarized, “It’s not just about human-to-machine interfaces anymore. We’re moving toward human-to-human-like interfaces interacting with other machines. It’s a whole new way of thinking.”
Their insights offered a compelling roadmap for companies navigating the complexities of AI integration, underscoring the importance of data readiness, human-centric design, and adaptability in this era of rapid technological evolution.
