Automation has become a top priority among industrial businesses in recent years — especially with the growth of automation software that can easily integrate with existing workflows. In this article, we will highlight the main driving factors behind this transformation and show you where CEOs and other executives across the oil and gas sector have readily embraced automation.
Cost Efficiency
Every CEO aims to increase profits while limiting expenditure; the right automation tools can do both. For example, oil and gas firms utilize this kind of software to adjust pressure, temperature, and flow to maximize throughput and productivity; they also use predictive maintenance to spot equipment issues early, letting teams fix them before they cost the company millions.
According to Vimal Kapur, CEO of Honeywell, automation has saved or generated a total of $10 trillion for companies. In the same piece, he remarked that a leading energy producer used their automated energy asset-reliability platform to save around $25 million in one year, also lowering maintenance costs by 25%. Though their clients remain anonymous, many top energy firms are open about using automation to explicitly reduce costs or boost ROI.
For example, Chevron uses AI to fine-tune drilling parameters in its Permian Basin operations, a strategy that has enabled the company to reduce its spending by approximately 10%. CEO Mike Wirth was quick to clarify that this was about “[growing] more production while spending less,” a key part of any thriving automation strategy. Similarly, BP’s Ann Davies praised AI for letting the corporation “drill more wells per year.”
Quality Control
In the industrial sector, mistakes can cost millions. Even a slight mismatch in a pipeline’s flow or pressure risks a spill or rupture — luckily, automated sensors can tighten these parameters and ensure they stay within optimal levels. Not only does this add to automation’s cost-effectiveness, but it also ensures a smooth operation. This extends to decision-making; AI can create targeted recommendations that human operators then follow through on, but it’s all backed by data.
Here’s a rundown of how automation helps with quality control in oil and gas:
| Quality Control Area | How Automation Helps | Impact on QC Performance |
| Real-Time Monitoring | Sensors track pressure, flow rates, temperature, and oil/gas ratios. | Detects deviations early and ensures stable product quality |
| Drilling Quality | Automated drilling systems can take care of weight-on-bit and telemetry | Fewer human errors and better borehole stability |
| Emissions Detection | Methane detectors and other sensors continuously monitor for emissions | Faster leak identification and better environmental compliance |
| Integrity Monitoring | Smart pigs and SCADA systems can monitor cracks and flow anomalies | Faster detection of pipeline defects and a lower chance of contamination |
| Refining Process Control | Automated control loops will optimize temperature and chemical dosing | Improves product purity and helps minimize off-spec fuel batches |
| Digital Twins | Automatic simulations detect quality issues and test different approaches | Allows teams to check changes to their usual processes risk-free |
| Predictive Maintenance | AI models can detect degradation in equipment that affects its reliability | Teams can carry out repairs without any lengthy unplanned downtime |
| Traceability | Automatic event and process logs that outline decision chains | Better auditability, easier to reach the root cause of potential issues |
Future-Proofing
Many industrial CEOs have already integrated automation into their long-term plans — affording them a decisive advantage in a high-risk sector. Thomas Siebel, CEO of C3.ai, which partnered with Shell on various AI-driven solutions, said that any company that doesn’t “digitally transform themselves” will “cease to be competitive.” Similarly, Shell’s Dan Jeavons described digital tools as a “key lever” that can “transform the energy system” and help with net-zero targets.
Focusing more on Shell, the company’s global head of AI sees it as an investment in the future, rather than something that delivers 100% of its value today. Speaking on the company’s Insights blog, she remarked that it can be a “huge change exercise” that only works as “part of a process that drives wider change.” Essentially, it’s a commitment to delivering value; she’s quick to point out that it’s not a “silver bullet” that will instantly streamline every process.
To some companies, this means creating an AI model or automation software from scratch that perfectly matches their workflows. However, even a relatively simple tool can take weeks — and a significant investment — to develop. It’s best to investigate third-party tools that suit your firm’s specific niche as well as its broad automation needs. Even if it’s not a seamless fit, integration specialists can help tailor the software to suit exactly how your team will use it.
