Deep tech disruption: How advanced technologies are transforming businesses

CEOs, CIOs and CFOs are finding that “deep tech” is actively driving business innovation and profitability. From AI models that boost sales to robots that slash production costs, advanced technologies are transforming both top-line growth and bottom-line efficiency. 

Business leaders don’t need to be technology experts to grasp this shift; they need vision and urgency. As a business executive who has led ventures in areas such as space technology or data security and helped bridge research and industry, I’ve seen first-hand how rapidly deep tech is moving from the lab into the heart of business strategy. The takeaway is clear: embrace deep tech now, or risk being left behind by those who do. 

From lab to market at lightning speed  

Not long ago, cutting-edge research might take decades to translate into real-world products. Today, that timeline is shrinking dramatically. For example, generative AI went from research milestone to widespread business adoption in barely a year. An IDC study found that usage of generative AI jumped from 55% of surveyed companies in 2023 to 75% in 2024. This surge is fueled by unprecedented funding and support for deep tech ventures. 

The path from lab to market keeps shortening. Through the Zimin Institutes, which I helped establish, we’re translating academic research into commercial solutions. Lately, we have been seeing projects transitioning from early applied research to spinouts within 18 months. It was hard to imagine this pace 5-10 years ago. 

Meanwhile, annual global investment in deep tech quadrupled from $15B to over $60B in 2016–2020, signaling that investors see shorter paths to profit and indicating more technologies funded five or more years ago have now reached commercial readiness. 

Artificial intelligence: Driving ROI across the board 

AI is the poster child of deep tech making a direct impact on business performance. According to a recent IDC study, companies using AI are reporting an average of $3.70 in returns for every $1 invested, with some seeing over $10 in ROI. Those returns come from multiple fronts: AI boosts productivity (92% of AI users leverage it for productivity), enhances customer experience and even unlocks new revenue streams. In other words, AI helps in both growing the business and running it more efficiently. 

Specific use cases illustrate how AI drives value: 

• Customer engagement and sales: Retailers and banks use AI-driven personalization to recommend products and services, increasing conversion rates and customer loyalty. In finance, AI algorithms analyze customer data to upsell and cross-sell products at the right time, boosting revenue per customer. 
• Operational efficiency: Logistics firms employ AI route optimization, cutting fuel costs and improving delivery times. In manufacturing, AI-based predictive maintenance systems analyze sensor data from equipment to predict failures and reduce unplanned downtime. 
• Product and service innovation: Software companies now sell AI-driven analytics as products, automakers offer AI features (like driver assist or predictive maintenance) as differentiators and healthcare firms use AI to develop new diagnostics and personalized medicine. 

Crucially, the time and cost to implement AI have fallen. Many AI deployments now go from pilot to production in under eight months, and businesses start seeing value within 13 months. That’s a remarkably short horizon for ROI. No wonder nearly every CEO is talking about AI: those who lag in AI adoption risk falling behind competitors’ capabilities. 

Robotics: Automation reimagining productivity and costs 

Alongside AI, advanced robotics is delivering measurable ROI across industries. Factories and warehouses now look drastically different — human workers collaborate with robots on a massive scale. Over 4.28 million industrial robots operate worldwide, a record high and up 10% year-on-year. This robotic revolution directly boosts productivity, with robots performing tasks tirelessly and precisely. 

Integrating robots can cut manufacturing costs by 20% to 60%, while robotic system costs have fallen by over 50% in 30 years, allowing many manufacturers to achieve ROI in under two years. 

Robotics extends beyond factories into warehousing and logistics. Amazon employs hundreds of thousands of robots in fulfilment centers, enabling 75% faster inventory storage and 25% quicker order processing. Such efficiency directly drives top-line growth, enabling faster deliveries, attracting customers and controlling costs. Other retailers are rapidly following suit, deploying autonomous robots and piloting delivery drones. 

Beyond AI and robots: Emerging deep tech shaping industries today 

AI and robotics are the headliners, but other deep tech fields are rapidly reshaping industries: 

• Quantum computing: Banks and investment firms are testing quantum algorithms for portfolio optimization and risk analysis, seeking breakthroughs classical computing can’t achieve. Quantum services are already available via cloud platforms, addressing complex issues in chemistry and logistics. 
• Biotechnology and synthetic biology: The swift development of mRNA vaccines in 2020 illustrated biotech’s unprecedented speed in delivering transformative products. Pharma and agriculture companies now leverage AI and gene-editing (e.g., CRISPR) for personalized medicine and drought-resistant crops. 
• Satellite technology: Rapid growth in satellite constellations benefits telecom (remote connectivity), insurance and agriculture (high-resolution crop monitoring and disaster assessment). Even terrestrial industries gain from enhanced communication and data from space. 
• Advanced materials and energy: Innovations in materials science enable stronger, lighter, sustainable products — next-gen batteries for affordable EVs, improved airplane composites for fuel efficiency and clean-energy breakthroughs like small modular nuclear reactors and carbon capture technology.  

Each of these deep tech domains is reshaping industries in ways that drive competitive advantage — either by creating new products and services (top-line growth) or by solving problems that reduce costs and risks (bottom-line protection). Crucially, they often reinforce each other: advancements in one field (say, materials for better batteries) amplify innovation in another (say, more efficient electric vehicles), multiplying the impact on business. 

A strategic imperative: Integrate deep tech or fall behind 

If deep tech is so promising, why aren’t all organizations embracing it overnight? 

Key challenges include cultural resistance to change, talent gap and skills shortage, presence of legacy systems and costs considerations. Overcoming these challenges isn’t easy, but it’s feasible with the right approach. 

Some companies just don’t know where to begin. A major stumbling block is often quality data collection. Attempting advanced applications without digitizing foundational processes first leads to disappointments, too. 

To start, use this proven playbook: 

1. Complete data infrastructure audit (success hinges on treating data as a strategic asset) 

2. Launch 2-3 pilot projects 

3. Align the C-suite around the urgency and value of transformative innovation 

4. Allocate budget to deep tech 

Established companies adopting deep tech benefit from effective risk diversification, hedging against industry disruption. Many Fortune 500 companies now invest in AI, robotics and biotech startups through corporate venture arms, gaining insights and strategic advantage. 

Family businesses also increasingly allocate capital to deep tech innovation. Their patient capital, often being invested on 10+ year horizons, is a natural fit for deep tech’s longer development cycles. These investments can yield outsized returns when they find their way to corporations and consumers and buffer the family’s wealth against downturns in traditional sectors. 

It’s telling that deep tech technologies have grown to represent about 20% of venture capital funding, doubling from 10% a decade ago — a clear signal that savvy investors consider it a critical piece of a balanced portfolio. 

Deep tech as a core of business strategy 

Summarizing, the key reasons to embrace deep tech now are: 

• Competitive advantage: Early adopters set industry standards and attract customers while competitors lag behind
• Efficiency and cost leadership: AI and automation streamline operations, lower costs and improve margins even in highly competitive markets
• New revenue streams: Deep tech opens entirely new business models, like AI-driven services or smart products, diversifying income beyond traditional lines
• Resilience and futureproofing: Investing in deep tech builds agility and ensures businesses can quickly adapt to future disruptions, guarding against obsolescence
• Talent magnet: Finally, tech-forward companies attract top engineers and innovators, essential for long-term competitiveness

Here’s the visionary conclusion for any CEO, CIO or CFO reading this: imagine your industry five or ten years from now, reshaped by deep tech. Will your company lead that transformation or struggle to adapt? Integrating deep tech today positions your business for sustained success and growth. Those who embed deep tech into their core strategy will define the next era, while others risk falling behind. 

The choice — and the opportunity — is yours. 

Dr. Mark Shmulevich is the founder and managing partner at Aloniq, an early-stage deep-tech investment firm. The insights in this article draw from his experience scaling software businesses in the data protection and cybersecurity domain as well as investing in startups. Mark’s involvement with industry bodies like Singapore’s SGTech provides a unique perspective on the evolution and impact of cybersecurity strategies in today’s business environment and a direct view of the demand for vCISO services in the industry today.