OpenAI just launched a custom AI consulting offering, with a $10M per engagement minimum price tag. And I know exactly why they did it.
We all know that AI's potential is enormous, yet the way to win with AI is to embrace customization and deep integration. It is for this reason that I believe (and I’ve been running tech services companies for 25 years) that the entire software services industry is about to change for the foreseeable future.
Why Context and Customization Are Non-Negotiable
AI tools can seem deceptively plug-and-play at first glance. The glossy promise of pre-built models or APIs might tempt organizations seeking quick wins. However, as highlighted in Foundation Capital's report, The $4.6T Service-as-Software Opportunity, the one-size-fits-all approach rarely holds up in practice.
Effective AI systems require extensive tailoring to specific scenarios - a process that tailors generic models to specific scenarios. Industry regulations, customer preferences, and workflow peculiarities all play a role in shaping how AI should be applied.
For example, a finance firm leveraging AI for fraud detection must adapt its models to detect patterns unique to its business processes and regional compliance requirements. Similarly, in healthcare, AI systems need to be retrained on proprietary patient data to meet rigorous accuracy and privacy standards.
This shift demands a level of customization that goes beyond surface integrations. Organizations need to treat AI as a tool whose full potential is unlocked only when combined with human expertise and industry-specific insights.
Off-the-Shelf AI's Limitations
Standard AI solutions fall short in high-stakes environments for several reasons:
- Generic Outputs: Pre-trained models are built on broad datasets, which may not reflect the nuances of specialized industries.
- Data Blind Spots: Proprietary or legacy datasets are often excluded, leading to incomplete analyses.
- Workflow Mismatch: AI solutions without integration into existing processes create friction rather than boosting productivity.
The stakes for getting AI wrong are high. Misaligned models can render faulty predictions, confuse workflows, or even erode trust among employees and customers.
The Shift Toward Service as a Software
Instead of delivering one-off AI implementations, successful software service providers are evolving into creators of scalable, tailor-made AI solutions. These solutions effectively marry intellectual property with operational efficiency - a model sometimes referred to as Service as a Software (or SaaS 2.0).
The opportunity here is enormous, with the service layer surrounding AI expected to grow exponentially. Companies that thrive in this era will understand that AI is not a static product; it’s a living, evolving system requiring constant refinement.
Building Blocks for Transformative AI Integration
To fully realize AI’s potential and elevate it beyond a mere buzzword, organizations must focus on three critical tenets:
- Deep Customization
- Fine-tune models to reflect the specific needs of industries and customers.
- Engage domain experts to reinterpret proprietary data through an AI lens.
- Structure workflows to incorporate AI insights seamlessly, minimizing disruption.
- Outcome-Based Approaches
- Align pricing models to measurable business outcomes instead of rigid contracts.
- Focus on value delivery, whether improving speed-to-market for software or reducing IT costs through automation.
- Human Ethics and Collaboration
- Build systems guided by ethical principles, prioritizing transparency, accountability, and inclusivity.
- Combine high-quality consulting with scalable, ethical platform solutions supported by agile, caring teams.
A New Vision for Tech Services Companies
To succeed in this rapidly changing industry, software services companies must pivot from traditional mindsets. They need to blend three core elements to stay relevant and competitive:
- AI Intellectual Property + Agile Engineering: Develop proprietary AI capabilities as foundational value assets, supported by expert engineering teams capable of rapid iteration.
- Ethical Alignment to Outcomes: Ensure all AI solutions respect human ethics, foster trust, and are geared toward achieving practical, measurable results for clients.
- Global, Caring Teams: Success will come from diverse, collaborative teams that balance technical precision with empathy, regardless of location.
This model is not only achievable but also necessary in an era where customers increasingly demand better value, deeper insights, and more ethical transparency from service providers.
The Path Forward
The software services industry is truly the glue that’s enabling AI transformation. AI is revolutionizing what services companies can offer, but the future belongs to businesses that engage AI as a tool for profound, context-sensitive innovation.
By integrating AI into their DNA, aligning pricing to outcomes rather than services rendered, and maintaining their ethical compass, leaders in the space can redefine both their industry and their customers' success. After all, in an AI-powered world, it’s not technology alone that drives progress - it’s the strategic, human-centered vision behind it.
Debbie Madden
