20 Jul 2023

By BF Team

7-min read

Bridge Forum Summit 2023: Wrap Up

Bridge Forum Summit 2023: Key Takeaways

This article builds on the key takeaways from GIC’s Bridge Forum Summit 2023, held on May 9th & 10th in San Francisco. The two-day event, themed “A World in Transition,” provided a platform for preeminent visionaries, trailblazing entrepreneurs, and influential tech titans such as Marc Andreessen, Mustafa Suleyman, Dave DeWalt, Kelly Steckelberg, and many others to delve into the defining trends of today’s technology landscape: artificial intelligence (AI), data, and cybersecurity.


Generative AI is among the most important technological evolutions of the past decade, both because of its seemingly limitless applicability and the rapid pace at which it is advancing. It has led to an overnight paradigm shift as computers are learning to better understand their creators and have begun to exhibit human-like creativity with remarkable fidelity.

It is no longer in question that AI will unleash a profound, new wave of efficiency and productivity, relying on the intersection of previously theoretical technologies like neural networks and deep learning. This new wave of AI will redefine human-to-computer interaction in both our personal and professional lives, creating new opportunities for foundational AI-first systems that will shape the future of knowledge work, complex pattern recognition, sales and marketing, content generation, molecular development, disease diagnosis, software development, and countless other previously human-championed endeavors.

In advertising, AI can help companies personalize ad experiences by creating bespoke content almost instantaneously:

“Generative AI has allowed companies to fully automate the process of creating ads. For every product that companies want to advertise, AI will automatically generate tens of thousands, if not hundreds of thousands of ads, throw them all out onto an ad network, and the algorithm will automatically learn which ads perform the best, ultimately driving a huge return on ad spend.”
Alexandr Wang, Founder & CEO, Scale AI

As companies race to unlock the enormous potential value AI can deliver, sourcing technical talent with sufficient fluency across a wide range of needed, advanced engineering skills to fill AI-related roles has proved challenging.

“AI specialists are extremely rare and very expensive,” said Mustafa Suleyman, Co-Founder of DeepMind and Inflection AI. Companies will need to prioritize upskilling existing employees and look beyond traditional hiring practices to close the gap and build their competitive advantage in the market.

Beyond the demand for AI-proficient engineering, Suleyman also recognizes the profound change this technology will have on the future of work, noting that AI poses a greater risk to white-collar than blue collar jobs over the next decade, adding, “it’s much easier to automate those jobs.”

In the race to understand and utilize AI, Suleyman added that it is likely that we will see outcome disparities for various types of workers, companies, and industries:

“I think the question is whether people are able to adapt, learn new skills, take advantage of these new tools quickly enough, and how that transition is managed by governments and large organizations.”
Mustafa Suleyman, Co-Founder, DeepMind and Inflection AI

Important to note is that the efficiency, productivity, and revolutionary new technological order that AI is ushering in will not come without cost. It has also given rise to a host of unwanted consequences, concerns, and ethical questions, like privacy protection, training data ownership rights, the potential for expanding global inequality, and highly-targeted misinformation campaigns.

As is, reports of AI “hallucinations,” instances in which AI fabricates a created response rather than producing a factual output, are typically the result of insufficient or inaccurate training data. But Suleyman says, “[I am] very confident that we will soon overcome the vast majority of the hallucination problems” as companies transition to adopt this technology and make it more “succinct and precise.”

In the interim, for organizations, these types of risks are far-reaching, ranging from reputational damage and diminished public trust to national security concerns that could contribute to global instability. Singapore Deputy Prime Minister Heng Swee Keat noted the importance of proceeding with caution: “As we advance new technologies, we must breach the governance gaps. Tech innovation may sometimes run ahead of our ability to understand and properly harness it for good.”

It is critical that both businesses and governments identify and control key risks associated with AI through a multidisciplinary approach involving leaders in the C-suite and throughout the company to ensure front line vigilance is maintained.


Cybersecurity threats have never been more sophisticated, numerous, or multi-vectored than today. With more than 3500 known hacker networks, black hat actors are no longer limited to concentrated groups of individuals; they now include highly sophisticated, geographically diverse organizations that leverage integrated tools powered by AI and machine learning.

In 2023, global corporate cybersecurity spend is forecast to hit US$180 billion, up 11.3% YoY after a similar rise in the year prior.

Anticipation and preparation are key: organizations must proactively incorporate the proper protections and work to reinforce defenses before hackers strike to minimize adverse, costly outcomes.

According to Dave DeWalt, Founder & CEO of NightDragon and former CEO of McAfee and FireEye, employees provide uniquely vulnerable access points for cyber attacks, requiring education, literacy, and training to properly safeguard companies from the bottom up.

DeWalt cited an incident in which his previous company was tasked by a CEO of a large Fortune 500 institution to test its cyber defenses. He found that more than two-thirds of the company’s senior management email accounts were compromised through spear phishing attacks. The reason: the senior management’s executive assistants, who were responsible for managing their bosses’ inboxes, had clicked nefarious links: “What really occurred was a literacy problem: many of the assistants of those executives were clicking on the email, compromising the network.”

Gaps in employee knowledge and expertise reinforce the need for technological intervention to safeguard organizations. Maintaining an accurate “software bill of materials,” which documents all  open source and third-party elements present in a piece of software, and their patch status, can ensure  security teams are prepared for regulatory inquiries and can conduct thorough breach root cause analyses when problems occur, explained Jennifer Bisceglie, Founder & CEO of Interos.

Less understood, but of critical importance, is how partner and vendor vulnerabilities can compromise broader company systems. Bisceglie added: “Private sector companies are trying work with their suppliers to protect their software supply chain. And when suppliers fortify their own defenses, the whole supply chain gets stronger.”

While new technologies have helped to substantially augment hackers’ toolkits, the use of AI can also help companies spot pattern abnormalities and intelligently identify risky behavior amongst their employee base, empowering them to preempt attacks and protect their networks.

Sanjay Jeyakumar, Co-Founder & Chief Technology Officer of Abnormal Security, explains: “When you have a very persistent attacker, they can create highly targeted phishing campaigns. How do organizations go about stopping them? By using behavioral AI and using the behaviors of your organization to understand what’s normal and what is abnormal.”


The data revolution is underway and has completely upended traditional ways businesses extract, analyze, and rely on data to make decisions. Data cleaning, warehousing, routing, and observability have helped bring about a new era of quantitatively derived decision-making across organizations of all types.

Despite the recent influx of new sources of information and synthesis tools, many companies still struggle to operationalize this new resource and incorporate it into key business processes. Why? Legacy organizational structures and the lack of familiarity with next-generation analytics tools are at least partly to blame.

AI has successfully intersected with data analysis, allowing organizations to not only find answers faster, but also create transparency and clarity around processes. It is important for companies to formalize their efforts around data strategy, development, and implementation, and instill creative thinking about how to embed data into the heart of their organizations.

According to Barry McCardel, Co-Founder and CEO of Hex Technologies, this requires placing data analysts into operational units across the entire enterprise: “Maximizing ROI comes down to how your team is oriented and organized. Do data practitioners all sit together or are they embedded in the rest of the organization?… That’s where I think a lot of data teams can feel a little ‘ivory tower.’ And it’s probably the single biggest barrier that I see in companies feeling little impact from data, it’s that organizational friction and lack of alignment.”

Massive volumes of unstructured data are another challenge for enterprises who haven’t yet developed the capability to algorithmically organize their data. This is why we see data quality and governance exponentially growing in importance, especially for organizations using natural language processing and machine learning to aggregate and synthesize huge swaths of information.

“It’s important to think of data as a product. We’ve all aggregated so much data and now we need to make sense of it. One of the trends I’m seeing teams adopt, which is helpful and practical, is having product managers for data and having requirements defining the customer. As part of this, we can think about the governance around it and data quality.”
Barr Moses, Co-Founder & CEO, Monte Carlo


In this digital world, data science teams also need to work closely with domain experts in AI to extract the real value from data and allow for functionally focused employees to solve highly specific business problems to which they are uniquely suited to evaluate. McCardel agreed: “AI will free up data teams from the drudgery and tedium of the things they don’t want to be spending their time doing and focusing them on these really highly creative, uniquely human tasks.”

In summary, the tech landscape is shifting rapidly. The success of modern, global businesses will be determined by their abilities to embrace and incorporate emerging technologies like AI, harness and meaningfully utilize data, and effectively mitigate cyber risk. Read more in-depth reports from Bridge Forum Summit 2023 with key insights into what all businesses must think about as they prepare for a world in transition, here:

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