Which tech subsectors do you find most attractive?
Fundamentally, our strategy as a firm is to invest behind secular growth. Internally, we refer to our approach as transformational growth investing at scale. What that means in practice is that we look to identify themes that have staying power and are underpinned by high levels of demand and a fundamental mismatch with supply.
With that supply-demand dynamic in mind, there are several themes within technology that we find particularly interesting. Take cybersecurity. Cybersecurity has been a consistent top CIO priority over the last decade, driven by the increased frequency and growing sophistication of cyberattacks and changing threat landscape. The rise of cloud computing and the prevalence of remote working have further grown the attack surface, while the rapid growth of generative AI has increased its efficacy by personalising at scale.
As a firm, we have been repeat investors in this segment. Permira fund investments to date include Mimecast, a human risk and advance email security solution; BioCatch, a provider of behavioural biometrics technology; Sysdig, a cloud-security vendor; consumer security software company McAfee; and Exclusive Networks, the largest cybersecurity-focused value-added distributor globally.
Another sector we consider to be particularly attractive is the financial services end market, which is behind the curve on cloud adoption. We are in the early stages of digital modernisation at traditional financial institutions, which are still largely served by on-premise, legacy technology no longer able to fulfil customer needs in a digital era.
Permira’s investment in Clearwater Analytics is an example of native cloud tech that is replacing legacy incumbents, leveraging ‘product leadership’ and resulting in high customer satisfaction. Klarna, on the other hand, which funds from our growth equity strategy backed, is a good example of a disruptor built from the ground up to compete with traditional financial services vendors with a consumer and merchant value proposition.
Finally, I would point to healthcare technology with a 10+ year arc. There are few industries that concurrently face ageing population-related demand trends and a labour-driven supply crisis, while also operating in suboptimised systems undergoing business model shifts (to value-based care) and are early in the technology adoption curves.
This may well be the vertical that, in time, will produce more than 10x better outcomes with profound societal impacts, from drug development and patient outcomes all the way to back-office and payment systems. It’s an area where Permira can bring to bear its deep sector expertise across both healthcare and technology.
How important is digital transformation to your value creation strategy?
In our experience, at exit, companies with a strong digital backbone tend to command higher valuations due to their scalability, margins and future growth potential. Digital transformation is hence a cornerstone of our value creation strategy at Permira, applicable across all the sectors we invest in, not just technology. We have built deep value creation capabilities in fields including AI, data analytics, SEO, pricing and packaging, go-tomarket optimisation, and more, to help our portfolio companies drive this incremental value.
The application of digital value creation levers outside of software can be particularly interesting. We see a number of sectors, such as services, that have a high density of manual interaction and where digital adoption can be used to help services businesses compete against companies that will likely not have the same digital backbone that most software businesses have today.
How do you approach tech investing?
We adopt a product-first approach, which simply means investing in companies that have established a genuine product-market fit by delivering truly differentiated product capabilities in their respective fields. These companies tend to be, or grow into, market leaders and are often category creators in their sectors.
The way we like to think about it is that we want to build not just bigger, but also better businesses over a sustained period. In that context, we believe those companies that offer the best products, and can ship better product faster, will be long-term winners as they typically enjoy customer loyalty, scalability and network effects, as well as having a deeply ingrained culture of innovation and pushing boundaries.
In our technology practice, we focus on the product, and we do that assessment first. If that checks out, we are ready to invest behind scaling the go-to market organisation, but not the other way around. We see a lot of businesses where the moat relies largely on go-to market rather than product capabilities – we believe these are the companies that in a generative AI world offer less upside and more downside risk.
What role do you see generative AI playing?
In October, the Nobel Prize for Physics was awarded to two scientists known as the ‘Godfathers of AI’, while the Nobel Price for Chemistry was awarded to work performed with an AI model for protein-structure prediction. Just as the internet, mobile and the cloud revolutionised the enterprise software landscape through driving product velocity, unleashing new functionality and shifting adoption curves, we believe that generative AI will do the same, if not more.
We have seen over the last 18-24 months how the cost of inference is dramatically falling, probably faster than anything we have seen in prior technology waves. Companies that integrate AI thoughtfully into their products will be better positioned to achieve defensible and sustainable growth, and to be leaders in the next wave of digital transformation. And those that are left behind will likely become legacy players faster than in previous cycles.
A number of market participants are treating AI as a product implementation exercise and miss the behavioural change that is required to drive the ROI. To be implemented successfully, AI requires process, workflow and behavioural changes that take time to effect – and if you look back at the history of technology, that time gap is typically longer than hoped for but shorter than linear thinking assumes.
Over the last few years, we have spent a lot of time focused on using our portfolio of over 35 software and technology companies as a laboratory to rapidly prototype potential solutions, then share the learnings across the portfolio more broadly. The percentage of R&D budgets within the portfolio that is earmarked for generative AI initiatives is growing rapidly, now a double-digit percent contribution, and we have taken the view that this offers an asymmetric risk-return profile.
Permira’s entire technology portfolio today is working on live generative AI projects and/or have rolled out coding assistant tools across its engineering organisations. We also have a very active AI community that brings together more than 200 technology and AI leaders from across our portfolio. The objective is to facilitate meaningful connections, share knowledge, and promote best practices across areas such as tech, talent, architecture and product management. Members are encouraged to highlight high-impact use cases and examples of applying AI technology at scale, as well as share lessons learned from when things didn’t go as planned.
At Permira, we also have a unique purview in AI adoption, through our funds’ portfolio of customer experience businesses, a segment that is at the front end of the adoption curve. At Zendesk, more than 10,000 customers today use AI Agents to resolve up to 80 percent of their tickets autonomously.
Zendesk has also become the first provider in the customer experience space to introduce outcome-based pricing for its AI-powered agents, allowing customers to pay only for resolved issues. Likewise, more than 40 percent of the nearly 6,000 Genesys Cloud customers are using the platform’s AI capabilities driving great traction on its standalone AI products, which are up 2x year-on-year.
But beyond customer experience, we see AI capabilities being embedded deeply in products across the portfolio. Some examples include Mimecast, which built a detection engine to identify whether a message is human or AI-generated, and layers AI to inspect the contents of an email, leveraging natural language AI.
McAfee has developed a deep fake detector that uses a deep neural network model to detect and notify individuals when audio or video content has been manipulated by AI. Seismic has developed a product called Aura Copilot, that handles the behind-the-scenes workloads for go-to-market teams. And lastly, Reorg has announced new features for instant intelligence summaries, automated credit rating reports, and flash earnings report generation, leveraging generative AI.
What trends are you observing in tech M&A?
Thematic origination has become a dominant modality for us. The days of relying solely on traditional LBO strategies are over. GPs are developing from providers of capital to strategic builders of assets with specialist capabilities. For us, this has meant remaining highly selective on the businesses and teams we back, bringing real industry expertise to the table to help companies develop their value proposition, expand market reach and accelerate growth, as well as providing the operational expertise to optimise profitability and improve efficiencies.
Within technology at Permira, we have a subsector-focused investment philosophy across both our buyout and growth equity funds, which we believe enables us to develop a better view of both incumbent profit pools and disruptor opportunities.
We also have a very strong and well-integrated bench of senior advisers working with us and our portfolio companies, including Bruce Chizen, former CEO of Adobe; Carolyn Everson, a former senior executive at Facebook; Andy Eckert, former CEO at Zelis; Simon Segars, former CEO of Arm; and Amol Kulkarni, previously CTPO of CrowdStrike. The knowledge and networks that these individuals bring to the table are powerful differentiators in today’s competitive landscape.
How are tech trends impacting investments in non-tech sectors?
Some of the more exciting and interesting areas to invest today are actually outside of the technology sector, for example B2B services across different vertical markets. For us, we can combine four decades of pattern recognition in technology with our deep, multi-sector specialisation to identify companies that offer asymmetric upside if they strategically invest in their digitalisation efforts and automation capabilities.
Take healthcare. Integrating AI into medical radiology can significantly enhance diagnostic accuracy. One of our funds’ portfolio companies, I-MED, has recently launched a generative AI initiative, leveraging more than 20 years of data to help radiologists process X-rays with greater speed and precision.
Other non-tech examples include legal services player Axiom, which is integrating generative AI to drive increased sales conversion, and knowledge process outsourcing business Acuity, which developed generative AI-enabled tools to augment analysts, resulting in a 10-30 percent increase in efficiency.
The hyperscale cloud vendors today have a power problem – data centres consume 1-2 percent of global power, but this percentage will inexorably rise by the end of the decade and will require substantial capital. A ChatGPT query needs over 10 times as much electricity to process as a traditional Google search, depending on the model size and server infrastructure. Private capital can help resolve some of these challenges by investing behind other energy resources.
