How Collectiv is Advancing Data & AI Under Darren Goonawardana’s Leadership

Kivo Daily Staff on April 3, 2025

By: Kathy Richards

A New Era of Business Intelligence

In today’s data-driven world, organizations are increasingly searching for ways to unlock insights, optimize decision-making, and integrate AI into their operations. Few companies have made notable strides in this space, like Collectiv— a Microsoft consulting company that has built a strong reputation as a high-ranked Power BI firm. At the helm of this transformation is Darren Goonawardana, a visionary entrepreneur shaping how businesses approach analytics, planning, automation, and AI.

His leadership and strategic insights have helped position Collectiv as a go-to firm for companies seeking to harness the power of Microsoft’s data technology ecosystem, guiding them toward data-driven decisions that are efficiency-focused and better prepared for future needs.

From Startups to Scaling a Global Consulting Firm

Goonawardana’s entrepreneurial journey spans over three decades, during which he has built companies on four continents and played a role in developing AI-driven business intelligence solutions. He co-founded Collectiv in 2019, growing it into a trusted strategic partner for enterprises navigating the Microsoft data ecosystem.

Collectiv’s expertise lies in addressing complex data challenges and delivering actionable solutions, helping clients build robust data architectures, automate reporting, and leverage AI for improved forecasting. The firm’s client-centric approach ensures businesses are not just collecting data, but making more effective use of it.

Goonawardana is passionate about simplifying how businesses interact with technology. He envisions a future where AI handles repetitive and complex tasks, while human intelligence is reserved for creativity, strategy, and leadership. With a global perspective and hands-on experience across multiple industries, he has built a firm that understands the unique data challenges companies face and offers tailored solutions that can drive measurable impact.

Beyond the technical aspects, Goonawardana brings a deep understanding of business psychology and leadership dynamics. He recognizes that many executives hesitate to embrace AI due to misconceptions about its complexity or potential risks. Through Collectiv’s consulting services and thought leadership, he actively works to educate leaders on how to integrate AI without disrupting their core business models, aiming for maximum efficiency with minimal friction.

What Makes Collectiv Unique?

While many consultancies offer generic data services, Collectiv distinguishes itself by providing highly specialized Microsoft data-centric solutions, including:

Full-scale Power BI / Fabric consulting & strategy
AI-driven business intelligence & automation
Custom data architecture for enterprises
Modernized planning & forecasting solutions
Executive coaching on AI and automation adoption

As AI continues to disrupt industries, Goonawardana is working toward positioning Collectiv as a leader in AI-driven business strategy. He suggests that companies that fail to embrace AI and automation could face challenges in the coming years.

A key differentiator for Collectiv is its end-to-end approach. Instead of simply deploying Power BI solutions, the firm ensures that organizations develop a robust data infrastructure, streamlined workflows, and scalable AI-driven insights that support sustainable growth. This commitment to holistic transformation helps establish Collectiv as a valuable strategic partner, not just a service provider.

Moreover, Goonawardana has made it a priority to foster a culture of continuous learning within Collectiv. The firm regularly trains teams on the latest AI innovations, automation trends, and Microsoft advancements, helping clients stay updated with cutting-edge solutions that support their competitive edge.

The “Cyborg CEO”

One of Goonawardana’s captivating insights is the idea of a “Cyborg CEO”—a leader who utilizes automation and AI to optimize business operations without being consumed by them. His belief is that executives should not be shackled to their companies but should use technology to create greater freedom, efficiency, and work-life balance.

By strategically leveraging AI, business leaders can focus on what truly matters—innovation, leadership, and vision—rather than getting bogged down in manual processes. Collectiv enables executives to embrace AI in a way that enhances their decision-making rather than replacing human judgment.

“AI isn’t here to take over your business—it’s here to give you back your time,” Goonawardana explains. His mission is to educate executives on how to integrate AI into their workflows, minimizing manual inefficiencies and potentially unlocking a new level of strategic decision-making.

From Data to AI: The Future of Business

As AI continues to evolve, Collectiv is intensifying its efforts to help organizations prepare for the future. The consulting industry, according to Goonawardana, is on the brink of transformation, and traditional firms may soon face competition from AI-driven advisory services.

His expectation? The future of professional services will be defined by automation, AI-powered insights, and self-service data intelligence. Companies that fail to adapt might struggle, while those embracing these changes will likely see growth.

One area where Collectiv is starting to make a significant impact is financial planning and forecasting. By integrating AI-driven predictive analytics, businesses can better anticipate market shifts, optimize budgets, and identify revenue opportunities in real-time. This capability has been helpful for CFOs and financial leaders who need reliable, data-backed insights to guide corporate strategy.

Additionally, Goonawardana is focused on expanding Collectiv’s role in AI governance and ethics. As more organizations adopt AI-driven decision-making, the need for responsible AI implementation is becoming even more crucial. Collectiv is actively working to ensure that AI models are not only efficient but also transparent, fair, and aligned with ethical business practices.

A Thought Leader in the Making

Beyond running Collectiv, Goonawardana is focused on building his personal brand as a thought leader. His interests span travel, AI’s impact on business, and executive efficiency hacks. He is also working on expanding his presence as a keynote speaker, sharing insights on AI, data-driven leadership, and the changing landscape of consulting.

With a global perspective, a passion for AI automation, and a track record of success, Goonawardana is not just leading a company—he’s influencing how businesses leverage data and technology.

To connect with Darren Goonawardana, visit his LinkedIn profile or explore how Collectiv is transforming business intelligence at gocollectiv.com.

Published by Joseph T.

Tech Giants and Their Influence on AI Research

Kivo Daily Staff 2 on April 3, 2025

Artificial intelligence (AI) has become one of the most transformative technologies of the 21st century, with applications spanning industries from healthcare to finance. At the forefront of this revolution are tech giants such as Google, Microsoft, Amazon, Meta, and Apple. These companies wield significant influence over AI research through financial investments, infrastructure control, talent acquisition, and policy advocacy. This article explores the various ways in which tech giants shape AI research and the ethical, economic, and societal implications of their dominance.

Financial Dominance in AI Research

Massive Investments

Tech giants allocate vast financial resources to AI research, funding the development of new algorithms, data models, and machine learning techniques. Industry analysts estimate that AI spending among major corporations will surpass a quarter trillion dollars annually. These investments not only fuel innovation but also shape the direction of AI research, favoring projects with commercial viability.

Funding Academic Research

A significant proportion of AI research conducted at universities receives financial backing from major tech firms. Professors and research teams at top institutions frequently collaborate with industry sponsors, benefiting from grants and access to proprietary datasets. However, this arrangement raises concerns about corporate influence over academic research agendas and the potential for conflicts of interest.

Control Over AI Infrastructure

Data Centers and Computing Power

Tech giants own and operate large-scale data centers equipped with specialized AI chips and supercomputing capabilities. These infrastructures provide the necessary computational power for training complex machine learning models, an essential component of AI research. Smaller research institutions and startups often rely on cloud computing services from these companies, making them dependent on industry-controlled resources.

Cloud Computing Services

Companies such as Amazon Web Services (AWS), Google Cloud, and Microsoft Azure offer cloud-based AI services, providing researchers with scalable computing power. While this lowers entry barriers for AI development, it also consolidates control over AI infrastructure in the hands of a few corporations. This dominance can limit independent AI research efforts and reinforce the monopolistic power of tech giants.

Talent Acquisition and Brain Drain

Hiring Top Researchers

Tech giants aggressively recruit top AI talent from academia, offering lucrative salaries, extensive resources, and opportunities to work on groundbreaking projects. Researchers specializing in deep learning, natural language processing, and computer vision are particularly sought after. As a result, industry labs attract many of the brightest minds, sometimes at the expense of academic institutions.

Impact on Academia

The exodus of AI researchers from academia to the private sector has raised concerns about the long-term sustainability of independent AI research. With fewer experts remaining in educational institutions, universities may struggle to produce unbiased and fundamental research that does not align with corporate interests. This shift could lead to an overemphasis on AI applications that serve commercial rather than societal needs.

Influence on Research Agendas

Setting Priorities

Through their funding initiatives and research partnerships, tech giants can shape AI research priorities. Projects that align with corporate goals—such as improving recommendation algorithms, automating customer service, or enhancing targeted advertising—tend to receive more funding and attention. In contrast, AI research aimed at addressing societal issues, such as reducing algorithmic bias or improving transparency, may receive comparatively less investment.

Publication and Patenting

Many influential AI research papers are authored by researchers affiliated with major tech companies. While some findings are shared openly with the research community, others are protected through patents, limiting public access to cutting-edge advancements. This dual approach of promoting open research while safeguarding proprietary technologies underscores the competitive nature of AI development.

Ethical and Societal Implications

Bias and Fairness

AI systems developed by tech giants have faced criticism for perpetuating biases present in training data. Algorithmic discrimination has been observed in hiring tools, facial recognition systems, and predictive policing applications. Ensuring fairness in AI models requires increased transparency, better data curation, and continuous monitoring, yet these measures may not always align with corporate priorities.

Regulatory Influence

Tech giants actively participate in shaping AI regulations and policies by lobbying governments and contributing to AI ethics committees. While this involvement can drive the adoption of responsible AI practices, it also raises concerns about regulatory capture, where corporate interests influence public policy decisions. Striking a balance between industry expertise and unbiased policymaking remains a challenge.

Open Source and Collaboration

OpenAI and Partnerships

Collaborative initiatives, such as OpenAI’s partnerships with Microsoft and Google’s TensorFlow project, exemplify the benefits of industry-backed AI research. These collaborations have led to the development of widely used AI frameworks and tools, democratizing access to AI capabilities.

Balancing Openness and Proprietary Interests

Despite promoting open-source AI tools, tech giants also safeguard their proprietary technologies. While open-source contributions foster innovation and inclusivity, critical advancements in AI—such as state-of-the-art language models and neural networks—are often kept behind closed doors, reinforcing competitive advantages for industry leaders.

Global AI Leadership

Geopolitical Dynamics

The dominance of U.S.-based tech giants in AI research contributes to geopolitical power dynamics, influencing international AI policies and collaborations. Countries such as China, through companies like Tencent and Alibaba, are emerging as AI powerhouses, intensifying global competition.

Competition with Emerging Markets

While Western tech firms lead in AI research and development, emerging markets are making significant strides. Governments in regions such as the Middle East and Southeast Asia are investing heavily in AI initiatives, challenging the dominance of traditional tech giants and diversifying AI research contributions.

Tech giants play a crucial role in shaping AI research, driving innovation through financial investments, infrastructure control, and talent acquisition. However, their influence also raises concerns about monopolization, ethical implications, and regulatory challenges. As AI continues to evolve, ensuring a balanced approach that promotes open research, equitable access, and ethical considerations will be essential. By fostering collaboration between industry, academia, and policymakers, the AI landscape can remain inclusive, transparent, and beneficial to society at large.

Day: April 3, 2025

Follow us on: