The rise of AI services
For more than 20 years I worked in a variety of high-tech companies delivering solutions across a range of industries. In that time, one of the key strategic challenges I experienced was finding the right balance between product-focused and services-oriented strategies. Then dealing with the tension that arose when we got that wrong. It’s a dynamic that plays out in many forms, but with a common underlying cause – a perception that true innovation and scale can only come from “pure” software or technology products, while services firms are somehow “second class” consultancies or delivery partners.
I saw this first hand in my work at IBM. During my time there, the product groups and service delivery teams were largely separated. This division, while useful from an internal management perspective, caused numerous issues at customer sites, where success required bringing together innovative technologies with intuitive delivery skills to meet the client’s needs. With very different goals and objectives in play, the challenge was to harmonize these two aspects to ensure success. Unfortunately, this didn’t aways happen…and rarely without a lot of blood, sweat, and tears…
In the end, the way forward inevitably involved combining the strengths of both teams by embedding product engineers directly with service engineers, deeply understanding client workflows and pain points to customize the technology to fit with the local context. Or conversely, seconding experienced field service engineers to spend time with the product teams to expand their client knowledge and guide their feature release priorities.
With this experience in mind, I was particularly intrigued to read of the insights from 8VC with leading AI company Palantir as they worked with customers to deliver AI solutions. What has been their experiences of balancing product and service elements of AI delivery? Do their lessons from successful AI solutions delivery mirror my own at IBM and elsewhere?
The spark for reconsidering AI services was a recently published article from 8VC, a new technology investment company with significant experience funding AI-based organization. In that review they provide many important reflections on the success criteria that drives their investments in AI companies.
Their conclusion is that it is software combined with human expertise, not just automation, that is the key for tech-based product-and-services companies to thrive. This observation allows them to propose some simple but challenging principles for building such businesses, which echo past successful investment strategies.
Fundamental to their argument is that a services-led, domain-specific approach is becoming increasingly relevant – and essential – as AI and related transformative technologies continue to evolve. They believe that the real opportunity lies in combining these powerful digital tools with expert human operations to fundamentally reinvent entire service industries. By tightly integrating software and services, companies can not only improve margins and scalability, but truly transform how work gets done for their customers.
This shift has profound implications for digital leaders. It means rethinking the role of services within our organizations, moving it beyond a support function and cultivating it as a strategic capability that shapes product roadmaps and growth trajectories. It requires investing in the right talent and operating models to seamlessly blend technological and operational excellence. And it may even mean being much more open to inorganic strategies that can rapidly expand an organization’s reach and impact.
The rise of AI-powered services represents a fundamental shift in how we think about the relationship between software and the real-world problems it is meant to solve. As the 8VC article explores in depth, the true value lies in deeply understanding our customers’ domains, embedding our solutions within their workflows, and continuously improving outcomes through the interplay of automation and human expertise. Digital leaders who embrace this services-led, domain-driven approach will be best positioned to thrive in the decade ahead.
It’s a message that others also support. For instance, the importance of AI services is highlighted by McKinsey in the way they are advising their clients deploying AI at scale. They focus on a key aspect for all organizations: Improving customer service.
Customer service has proven to be a critical driver of business growth, with McKinsey’s data indicating that companies that excel in this area achieving twice the revenue growth of their peers. However, delivering exceptional customer service traditionally requires significant investments in skilled staff, management, and technical resources – a challenge made more difficult by current economic pressures and labour market constraints.
As a result, McKinsey believes that new technologies, particularly GenAI and other digital tools, offer a potential solution to this paradox by enabling both improved efficiency and enhanced personalization. However, they also recognize that companies must avoid common pitfalls in their digital transformation efforts, such as taking an overly cautious, piecemeal approach or relying too heavily on a single technology as a “silver bullet.” Instead, successful organizations are deploying an integrated toolbox of technologies at the right time and in the right way, while simultaneously improving their underlying business processes.
The key to success, in McKinsey’s view, lies in a three-pronged approach:
When done correctly, this creates a virtuous circle where efficiency gains free up resources for further service improvements, leading to sustainable competitive advantage and growth. This includes implementing continuous learning programs and enabling frontline employees to use low-code/no-code platforms for process improvement
Yet, making progress with AI-at-Scale is far from straightforward. While advanced AI technologies promise efficient, low-cost customer experiences, the true challenge lies in building service organizations capable of harnessing these tools to their full potential. The key insight from both McKinsey and the 8VC reflection on Palantir is that across many complex, highly-regulated, and specialized domains, a “pure product” approach is insufficient. Instead, a hybrid model that tightly integrates software and operations can be far more effective. Echoing my IBM experiences, 8VC illustrates this with Palantir’s “Forward Deployed Engineers” embedded directly with customers to deeply understand their workflows, data, and pain points. This allowed Palantir to iteratively improve its platform and deliver significantly more value than a traditional “software-only” vendor could.
Furthermore, we see this approach growing in relevance as AI and language models become more powerful. While point solutions that embed LLMs can be useful, the real opportunity lies in combining these technologies with expert human operations to transform entire service industries. We can see examples of this in practice across domains such as healthcare, logistics, and insurance where tech-enabled service providers are displacing legacy providers by delivering faster, cheaper, and higher-quality outcomes.
So, how can organizations adjust to a service-led approach to AI? The 8VC article highlights four core principles that offer important lessons to be adopted by all organizations seeking to adopt AI-at-Scale:
Driving technology-driven change requires a balanced combination of product deployment and service delivery. This is just as important in providing AI-at Scale. The review by 8VC concluded that central to Palantir’s successful AI strategy was the realization that services should not be seen as a necessary evil or afterthought. Instead, they are an essential driver of value – both for customers and for the businesses providing AI solutions at scale. By deeply understanding their customers’ operations and combining software automation with human expertise, tech-services companies can not only improve margins and scalability, but fundamentally transform how work gets done.
This has profound implications for digital leaders across all sectors. In practice it means rethinking the role of services within your organization –- moving beyond a support function and instead cultivating it as a strategic capability that shapes your product roadmap and growth trajectory. It means investing in the right talent and operating model to seamlessly blend technological and operational excellence. And it means being open to inorganic strategies that can rapidly expand your reach and impact.
Ultimately, the rise of AI-powered services reinforces previous experiences in how we think about the relationship between software and the real-world problems it is meant to solve. It’s no longer enough to just build clever algorithms or elegant user interfaces. The true value lies in deeply understanding a customer’s domain, embedding solutions within their workflows, and continuously improving outcomes through the interplay of automation and human expertise. Digital leaders who embrace this AI services-led approach will be best positioned to not just survive, but to thrive in the AI-driven decade ahead.
Originally posted here
