Automation has become a central theme in enhancing operational efficiency and reducing costs across various industries, notably in oil and gas operations as well as in the financial sector. Companies are increasingly adopting AI and automation technologies to improve processes, optimise performance, and navigate the changing workforce landscape.
In the oil and gas sector, digital tools are aiding operational performance by automating manual and resource-intensive tasks, enabling better data visibility and minimising human involvement in hazardous situations. A study conducted by GlobalData revealed that among over 230 professionals from more than 50 countries, half expect their organisations to increase investments in automation over the coming year. This aligns with a broader positive sentiment towards such technologies, which are seen as crucial for future operational viability. As seasoned field workers retire or transition to less risky jobs, the call for automation in the sector intensifies. Many firms are committing parts of their budgets to implement solutions like robotics, artificial intelligence, and the Internet of Things, recognising the long-term necessity for automation to remain competitive.
However, opinions vary on investment strategies. While nearly two-fifths of respondents anticipate a decline in their organisations' spending on automation technologies, attributed to different financial cycles or competing strategic priorities such as acquisitions, around 12% plan to maintain their current spending levels. The remaining respondents were uncertain, illustrating a mixed outlook on automation investments in the oil and gas industry.
In the financial sector, the momentum towards automation is similarly apparent, as highlighted by a report from SmartStream in collaboration with Acuiti Management Intelligence. The report underscores a significant shift in how firms manage reference data related to trade data, with 71% of firms investing in this area over the past five years, largely driven by automation. The hallmark of this change has been the marked reduction in manual processes, with 56% of firms reporting improvements in reconciliations and trade workflows. According to Ross Lancaster, head of research at Acuiti, this evolution reflects an expanded role for reference data beyond traditional reconciliation tasks, enabling firms to enhance efficiency and generate alpha throughout the trade lifecycle.
While 24% of financial firms have successfully fully automated their reconciliation systems, challenges remain, particularly in the standardisation of external data, which 46% of respondents identified as a significant hurdle. Furthermore, the adoption of AI technologies for data management is on the rise, with 25% of firms already utilising AI or machine learning, while an additional 30% plan to do so soon.
Linda Coffman, Executive Vice President at SmartStream RDS, noted the ongoing complexities inherent in integrating data from various vendors amidst the inconsistency of external counterparties and exchanges. Despite these challenges, the adoption of AI is transforming the use of reference data, paving the way for more sophisticated applications within the trade lifecycle. The trend towards continuous investment in reference data, moving away from sporadic upgrades, signifies a growing recognition of the importance of robust data management in mitigating risk and achieving operational excellence across the financial arena.
This convergence towards AI and automation stands as a testimony to how industries are reshaping their operational frameworks to adapt to modern challenges, showing a commitment to technological advancements that promise improved efficiency and safety.
Source: Noah Wire Services