53% growth of intelligent automation in the oil and gas industry

The majority of oil and gas companies globally are distressed with their current manual operating systems. Businesses are implementing Robotic Process Automation (RPA) and embracing other primary automation technologies to digitalise their core assets for favourable outcomes.


The Deloitte Global RPA Survey 2021 suggested over 53% of businesses have already commenced their automation journey, with the first movers having earned 4 times the return on investment. It is expected automation will achieve 'Universal Adoption' if the RPA growth rates remain consistent in the next five years and if availability structured data can be fast-tracked.

According to research conducted by CX Live in 2021, the most popular structured data applications are data analytics, IA and business process management, and machine learning.   As per Mordor Intelligence, the investment in AI by oil and gas companies was valued at USD 2,040.89 million in 2019, and it is expected to reach a value of USD 3,349.89 million by 2026 while registering a CAGR of 10.14% during the forecast period (2021-2026).
IA offers an advanced way to leverage diverse data streams for critical insights and deliver enterprise-wide connectivity.

According to research conducted by CX Live in 2021, the most popular structured data applications are data analytics, IA and business process management, and machine learning.


As per Mordor Intelligence, the investment in AI by oil and gas companies was valued at USD 2,040.89 million in 2019, and it is expected to reach a value of USD 3,349.89 million by 2026 while registering a CAGR of 10.14% during the forecast period (2021-2026).


How to accelerate IA adoption in Oil and Gas?


Most innovative enterprises commenced their automation journey with routine and rules-based tasks. Subsequently, they expanded whilst drawing self-learning by:

  • Incorporating artificial intelligence and machine learning architecture

  • Inserting layers of cross data utilisation and governance

  • Integrating functional and industry knowledge into automation initiatives

The data allows business leaders to analyse the benefits obtained from efficient and effective asset allocation, increase in production, reduction in employee burn-out, achieving higher safety levels and generating higher ROI.


The oil and gas industry already has a wealth of data from machinery such as logging tools, sensors, geophones to create comprehensive information sets that provide automation value. Yet, oil and gas companies have extremely heterogeneous and layered systems. Oftentimes, dozens of flows are not fully documented with diverse applications causing a lack of visibility into the underlying processes. IA offers an advanced way to leverage these data streams for critical insights and deliver enterprise-wide connectivity.


Oil and Gas have clear benefits in adopting intelligent automation across upstream, midstream, and downstream operations.


Upstream oil and gas Upstream activities prioritize enhancing exploration, ROI, and risk management at the vanguard.

  • Machine learning algorithms and AI control the precise drilling performance when optimizing opportunities by scanning and identifying the optimum property

  • Cutting-edge data management helps the field engineer with decision-making

  • IA provides continued analysis of problem situations and provides insights from a vast quantity of rich data

  • Virtual assistance or chatbots facilitate search optimization for field employees


Midstream and downstream oil and gas

In comparison to the upstream and downstream, mid-stream value chains have observed intelligent automation technologies to:

  • Manage manufacturing functions that provide system assistance such as inventory control, management, asset downtime management, supply chain monitoring, and generating insight at positive affect

  • Conversation automation enables NLP and NLG to add value to marketing and sales teams outcomes.

  • Technologies that cover conversation, vision, and intelligence have made a critical impact in recent times as the need for remote work increased substantially.


Environmental and Social Impact

Oil and gas players have to manage public perceptions and expectations of the environment and social factors especially with regards to toxic emissions. Because of significant accidents in this area, there have been financial and reputational losses for several energy companies. By leveraging IA organizations can:

  • Monitor carbon emission and control the predictive results from data-driven forecasts

  • Create environment, health, and safety (EHS personnel) for workers and prevent possible incidents

  • Give a flawless alert to EHS personnel when risks are expected to breach limited levels


Benefits from intelligent automation


IA systems extract data and precise data insight regeneration, resulting in efficient business implementation. Key advantages include:


Cost savings and productivity improvement:

IA runs with background data and is scalable quickly without increasing risk, compromising quality, or straining the existing workforce.


Consistent accuracy:

IA has a massive benefit in generating valuable data insight where the system pushes high probability decision-making. Also, AI is the system that can handle large volumes of tasks without hesitation, freeing up trained employees to focus on cutting edge innovation.


Enhance customer experience:

Enhancing business value, routing internal FAQs, maximising revenue by add-on products and services by agile reaction to market demands, and creating a positive customer experience thus creating a competitive advantage.


Increased scalability, agility, and continuity of service:

Intelligent automation enables numerous applications to access vast amounts of data in minutes thus providing faster and more accurate responses. It also allows employees to focus on revenue-generating tasks.


Intelligent automation value chain within an organization


The value of intelligent automation amplifies as interfaces allow for businesses to achieve efficiencies in their workflows. In the last couple of years, businesses have expedited digital transformation efforts, fueling more investments to support the automation of key business processes.


As the future of work evolves, roles will continue to grow, but low-level employment will be restructured to fulfil and measure these solutions and other higher-level tasks. Automation will bridge the skills gaps, and all stakeholders will need to adapt constantly to changing work situations.


The IA adoption is beneficial not only for the front line, service level functions but also for those functions where data volumes are high and data flow is relentless. It helps middle management to strengthen interconnection between stakeholders and discover the unknown in the business environment. There is no doubt IA will enable enterprises to stay competitive and determine the future of work. As a result, business leaders can reap triple wins ie cost redemption, efficiency gains and being future-ready.


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