How Oil & Gas Companies Must ‘Almost Be’ Software Companies to Compete in the AI Era
I was talking to someone last week who asked me a question that perfectly captures the challenge our industry faces: “JP, we want AI everywhere in our operations, but our IT team can barely keep our email running smoothly. How do we bridge that gap?”
The answer is uncomfortable but unavoidable: You can’t get to AI without a very strong digital team that can deliver and maintain digital assets for your organization. Your organization needs to look at digital competency as a foundational competency versus an administrative cost.
I’ve seen many times, in oil and gas, that the first thing to be cut is digital or IT spend because digital is not seen as core business. This needs to change. Does your organization need to be a software or IT company? Not necessarily, but it does have to be strong enough to create and maintain software, hardware, and other types of digital assets. If you don’t prioritize this spend, and treat the competency as importantly as any other strategic advantage, you’ll be stuck in the present—or maybe even in the past. You’ll be left behind by those who add digital as a strength.
To clarify what I said before: you don’t have to be a software or IT company… but you have to ‘almost be’ one.
The Digital Talent Crisis Is Real—And Getting Worse
The numbers paint a stark picture of what we’re up against. McKinsey research shows that large-scale digitization requires new talent, with digital projects needing software developers, data scientists, and “translators” who can turn analytical insights into operational actions. The rapid and ongoing digitization in the oil and gas industry means that competition for people with these skills is intense.
IBM’s research reveals that technical skills in AI, machine learning, automation, cybersecurity, cloud computing and systems architecture are the most in-demand, but these very niche technical skills expire or become outdated in around 2.5 years. The half-life for many technical skills is shortening, creating a gap between company needs and employee capabilities.
The global picture is even more sobering. According to the IMF, the tech talent shortage will swell to more than 85 million tech workers by 2030, which can potentially translate to lost revenue of over $8 trillion annually. The US Bureau of Labor Statistics mentions that between 2022 and 2030, the need for software developers will increase by 22%.
But here’s what really concerns me: it’s not just large technology companies that are searching for tech talent—industries like oil and gas are also looking for skilled people with advanced knowledge of AI, cybersecurity and data. We’re competing with Google and Microsoft for the same people.
The Industry Leaders Get It
The companies that are winning in digital transformation understand this reality and are acting accordingly. Saudi Aramco’s digital transformation program requires not only changing technology and operation paradigms but also a change in the nature and type of workforce competencies. Their Digital Workforce Program helps automate routine tasks while empowering employees to learn important new skills in AI and Big Data.
ExxonMobil has established data science centers where their data scientists work with digital teams to develop and deploy data-driven solutions and tools that are driving transformational changes in the way their sites are operated. As one ExxonMobil engineer explains: “Our data scientists work with digital teams in Houston to develop and deploy data-driven solutions and tools that are driving transformational changes in the way our sites are operated.”
Sidharth Mishra, Vice President at Wipro, captures the urgency perfectly: “To keep pace, energy companies need dynamic assessments that map GenAI solutions into existing use cases. The only way to vet feasibility in real time is to build deep internal GenAI capabilities.”
The “Administrative Cost” Trap
Here’s where most oil and gas companies get it wrong: they treat digital capabilities as an administrative function rather than a core competency. One midstream company reported that 65% of businesses identify the lack of IT talent and budget as top challenges when building and supporting custom business applications.
This mindset is killing competitive advantage before it even develops. IBM’s survey shows that 59% of oil and gas executives expect AI to contribute significantly to their revenue within three years, while 75% believe AI investments will deliver a measurable competitive advantage.
But here’s the reality check: more than half (56%) of executives say AI will enable new technology capabilities that fundamentally transform their business model. You can’t transform your business model with an “administrative” IT function.
What “Almost Being” a Software Company Looks Like
Let me be clear about what I mean by needing to “almost be” a software company. I’m not saying you need to start selling software to other companies. I’m saying you need to develop the internal capabilities to build, maintain, and evolve the digital assets that will power your AI-driven operations.
McKinsey’s analysis of successful digital transformations shows that future well organizations will build capabilities in areas such as agile coaching, data science, and advanced-tech stack planning. New capabilities can also lead to fulfillment and delivery of more ambitious targets.
This means having teams that can:
- Design and build custom applications for your specific operational needs
- Integrate AI and machine learning models into your existing systems
- Maintain and continuously improve digital platforms
- Ensure cybersecurity across all digital assets
- Scale digital solutions across global operations
The Competitive Reality
Dr. Susie, a Wipro executive with 33+ years in oil and gas consulting, warns: “While there are clearly very real risks related to GenAI, we believe the most dangerous risk is falling behind the innovation curve.”
IBM research shows that 67% of oil and gas executives say they are actively rearchitecting how they work to capture the full potential use of AI, and 58% report AI solutions can create significant value through new revenue streams. The companies making these transformations successful are the ones investing heavily in digital talent.
EY’s research emphasizes that oil and gas leaders don’t need to be able to build AI tools themselves, but they must be able to confidently communicate how AI can help the organization. But that communication becomes meaningless without teams capable of actually building and deploying those AI tools.
The Strategic Investment Framework
Based on my experience working with energy companies on digital transformation, here’s what building foundational digital competency actually requires:
Internal Core Team Development:
- Hire software developers, data scientists, and digital specialists who can train frontline teams in agile working methods
- Establish digital centers of excellence to develop and deploy the most promising digital use cases
- Build “translator” roles who can bridge operational expertise with technical implementation
Strategic Talent Acquisition:
- Adjust recruitment strategies, career paths, and employee value proposition to compete for digital talent
- Consider staff augmentation to supplement internal staff and speed up AI efforts with more total resources for development and implementation
Continuous Capability Building:
- Implement upskilling programs that build out employee skill sets through training and development programs to minimize skill gaps
- Create internal certification and training programs in data analysis, AI algorithms, and cybersecurity
The Cultural Transformation Challenge
Building digital competency isn’t just about hiring people—it’s about fundamentally changing how your organization thinks about technology. EY’s research shows that there is often cultural resistance to using AI tools or trusting their output, and this cultural resistance could be the biggest risk that oil and gas companies face.
McKinsey’s research shows that successful transformations require role modeling by management from the CEO down, communicating a compelling change story, structured capability building, and formal changes to processes and KPIs. Companies that apply all four elements are eight times more likely to achieve their change objectives.
The Cost of Inaction
Let me put this in terms that every oil and gas executive understands: opportunity cost. Companies that build strong digital competencies report measurable competitive advantages, while those that don’t find themselves increasingly unable to compete.
McKinsey research shows that companies viewing digitization as discrete, siloed projects often fail to achieve meaningful transformation. If management can’t see improvements in issues that matter to them, they will be unwilling to commit the resources necessary for widespread deployment.
The companies that continue to treat digital as an administrative cost center will find themselves in an increasingly untenable competitive position. As one successful transformation example shows, companies that deploy digital specialists across business units and establish comprehensive digital capabilities see transformational changes in how their operations function.
The Practical Path Forward
So what does this actually look like in practice? Based on successful implementations I’ve advised:
Phase 1: Foundation Building (6-12 months)
- Establish digital leadership at the C-suite level
- Hire core team of 5-10 digital specialists (software developers, data scientists)
- Implement programs such as internships and apprenticeships to build talent pipeline
- Begin cultural change management initiatives
Phase 2: Capability Scaling (12-24 months)
- Host “hackathons” across business units to identify potential digital use cases
- Build digital center of excellence
- Deploy digital specialists to train frontline teams in agile working methods
- Establish partnerships with technology companies for specialized needs
Phase 3: AI Readiness (18+ months)
- Deploy AI pilot projects with proven ROI
- Scale successful digital solutions across operations
- Build capabilities in areas such as agile coaching, data science, and advanced-tech stack planning
The Bottom Line
The AI revolution isn’t coming—it’s here. 70% of oil and gas executives agree that AI will improve their ability to navigate market disruptions. But AI without strong digital competency is like trying to build a skyscraper on a foundation of sand.
You don’t have to become Google or Microsoft. But you do have to build teams that can create, maintain, and evolve the digital assets that will power your AI-driven future. If you continue to treat digital competency as an administrative cost rather than a foundational capability, you won’t just miss the AI revolution—you’ll be left behind by it.
The question isn’t whether you can afford to invest in world-class digital teams. The question is whether you can afford not to.
JP Garcia is Founding Partner at Ashwood Advisory Group, specializing in helping energy companies build the digital competencies necessary for AI-driven transformation. He focuses on bridging the gap between operational excellence and technological innovation in complex industrial environments.
Ready to assess your organization’s digital competency and build the teams that will power your AI future? Contact Ashwood Advisory Group to discuss strategic approaches to building foundational digital capabilities that drive competitive advantage.
