A recent discussion on GIAI Square brought up concerns about networking opportunities in the SIAI 2.0 AI MBA program. While technical students focus on engineering and quantitative finance, business track students need a different kind of networking—one that connects them to venture capitalists, private equity firms, and AI-driven business leaders.

Unlike traditional business MBAs, where networking revolves around corporate job placements and HR-driven recruitment, the AI/DS industry demands a deeper understanding of technological realities. This article explores how business track students can build a valuable professional network that extends beyond superficial industry connections.

AI Investment and the Role of Business Track Students

SIAI’s business track does not train software engineers, but it does ensure that students understand the true mechanics of AI/DS projects. This exposure is critical for those aiming to work in:

• Venture Capital (VC): Assessing AI startups requires more than just reviewing pitch decks. Business track students should develop the ability to distinguish real AI capabilities from hype-driven marketing.
• Private Equity Funds (PEF): AI-focused PEFs need professionals who understand how AI can enhance operational efficiencies and financial performance, rather than just investing in ‘trendy’ AI companies.
• AI Strategy & Consulting: Business leaders who understand the limitations of AI can provide more effective strategic guidance than those who rely solely on buzzwords.

The Difference Between SIAI’s Business Track and Traditional STEM MBAs

There has been a rise in STEM MBA programs in the U.S., many of which provide only bootcamp-level AI training with little depth. Some prospective students might wonder: If business track students are not gaining hands-on AI/DS skills, how is this different from other MBA programs?

The key distinction is that SIAI’s business track provides exposure to real AI/DS research and development. Students do not merely learn surface-level programming or attend AI workshops; they engage with real AI/DS researchers and witness what separates serious AI/DS projects from bootcamp-level development.

This exposure allows them to:

• Discern the difference between commercialized, shallow AI solutions and research-driven AI models.
• Recognize what real AI/DS teams need in terms of business support and strategic planning.
• Avoid common investment pitfalls by understanding the depth required to execute successful AI-driven businesses.

Unlike traditional MBA graduates who may overestimate their AI literacy, SIAI business track students will not be fooled by superficial AI projects—they will develop a refined sense of what truly constitutes an AI-driven innovation.

Current Problems in AI Investment and How SIAI Graduates Can Stand Out

Many VCs and PEFs today—especially in less mature markets—lack the technical depth to evaluate AI startups properly. Instead, they:

• Follow the herd, investing in companies based on hype rather than substance.
• Rely on media narratives, without critically assessing the technology’s viability.
• Ignore deep industry research, instead making decisions based on networking events and investor consensus.

This lack of technical literacy often leads to poor investment choices, funding companies that lack true AI innovation while overlooking startups with real technical potential.

SIAI’s business track aims to close this knowledge gap, producing professionals who can:

• Assess AI/DS startups based on real technological value.
• Guide AI firms with strategic, well-informed business insights.
• Recognize AI-driven business models that are sustainable rather than speculative.

SIAI’s Approach to Business Networking

Networking in AI-driven industries is not just about knowing the right people—it’s about having the credibility to engage with top AI professionals and investors. To ensure business track students develop this credibility, SIAI’s networking approach includes:

• Connections with senior AI researchers and investors: Instead of focusing solely on HR networking events, students gain access to scientists and executives who shape AI business trends.
• Industry-based case studies: Students analyze real AI business models, learning how to separate meaningful innovations from unsustainable hype.
• GIAI’s Future Investment Arm: As part of its long-term vision, GIAI—the mother institution of SIAI—plans to launch its own investment vehicles, including a PEF/VC firm specializing in AI-driven businesses. This will provide business track students with real-world exposure to AI investments and potential career opportunities.

What Really Matters for Business Track Students?

Unlike traditional MBAs, success in AI/DS business leadership is not based on prestige or social capital alone. The best business professionals in this field:

• Understand AI/DS at a fundamental level.
• Can differentiate between real innovation and overhyped technology.
• Leverage technical credibility to earn the trust of AI founders and investors.

If you want to succeed in AI-driven business roles, your network must be built on knowledge and value, not just professional titles.

For Tech Track, please refer this twin article, Networking in AI: A Perspective for Technical Track Students | Global Institute of Artificial Intelligence.