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Automate to Accumulate: How AI-Based Business Process Automation Can Boost Your Bottom Line $£€¥

I have personally been accused of circumventing procedures in the past, albeit not in a maleficent way but because they were heavy, burdened and most of the times unnecessary. Such as asking a funding organisation a clean funds statement, when the funds are one and the same of the receiving institution. However, we cannot live without procedures, they are essential for business efficiency because they standardise workflows, reduce errors, and ensure consistency in operations. By streamlining tasks and minimising unnecessary steps, companies can enhance productivity and resource utilisation. This optimisation translates into higher bottom-line revenue, as businesses can better meet customer demands and operate cost-effectively.

For Large organisations especially with multi-nationals, these procedures sometimes take a life of their own with some being so archaic that with attrition have become a mystery to everyone, a beast that needs to be fed “because that’s how we do things around here”.

To make matters worse often these are lengthy and repetitive procedures due to the complexity of their operations and the need to maintain control over processes. While these procedures maintain compliance with industry regulations, ensure quality standards, and reduce the risk of costly mistakes, they can also lead to inefficiencies and hinder innovation.

With the recent emergence of generative AI and the democratization of machine learning, automating complex business procedures has become not only possible but also financially feasible. As the benefits of AI-driven automation now outweigh the costs associated with implementing such solutions, companies can experience a significant return on investment. In fact, according to a peer-reviewed study published in the Harvard Business Review, the adoption of machine learning and AI technologies has led to considerable cost savings and efficiency improvements across various industries, further validating the financial viability of these solutions.

It’s crucial to differentiate between business process automation (BPA) and AI business process automation to avoid falling into the trap of buzzwords. BPA is the automation of routine, rule-based tasks using software tools or applications, streamlining workflows, and increasing efficiency. In contrast, AI business process automation leverages machine learning and artificial intelligence to automate more complex tasks that involve decision-making, pattern recognition, and adaptation to changing conditions. By understanding these key distinctions, one can ensure that they utilize the appropriate terminology and concepts when discussing these different types of automation, thus avoiding confusion and maintaining clarity in communication.

As businesses continue to adopt machine learning and AI solutions, those that fully embrace these technologies will gain a significant competitive advantage. Automating repetitive tasks, improving decision-making, and enhancing customer experiences can boost profitability and maintain a competitive edge in the market.

Consider a large multinational corporation with a diverse range of products and services. One of the critical processes within this organisation is the management and approval of procurement requests, involving multiple departments and stakeholders. This complex procedure requires rigorous documentation and multiple levels of authorisation, leading to delays and inefficiencies.

By implementing AI-driven business process automation, the organisation can streamline this complex procurement process. Here’s how it could work:

  1. Data Consolidation: The AI system consolidates relevant information from various sources, such as enterprise resource planning (ERP) systems, supply chain management tools, and vendor databases, to provide a comprehensive view of the procurement landscape.
  2. Request Analysis: Machine learning algorithms analyse procurement requests to identify patterns, trends, and potential risks. This information helps the system route requests to the appropriate stakeholders and prioritise them based on urgency, compliance requirements, and other factors.
  3. Automated Approvals: Using predefined rules and guidelines, the AI system can automatically approve low-risk procurement requests, reducing the workload for human approvers and accelerating the overall approval process.
  4. Vendor Selection: The AI system evaluates vendor performance, pricing, and reliability data to recommend the most suitable suppliers for each procurement request. This enables the organisation to make data-driven decisions that optimise cost and quality.
  5. Continuous Improvement: As the AI system processes more procurement requests, it learns from the data and fine-tunes its recommendations and decision-making capabilities. This continuous improvement leads to enhanced efficiency and cost savings over time.

By automating this complex process, the organisation can reduce approval times, minimise the risk of non-compliance, and improve its ability to make data-driven decisions.

Let’s say that you want to join the party, what would be your first steps in this?

Always get advice from real experts. Just as an FYI people who say they are experts, usually aren’t. People who are really experts don’t need to say it out loud.

  • Assess the current state and identify high-impact processes: Conduct a thorough analysis of existing processes and focus on those with the most significant effect on productivity, customer satisfaction, and the bottom line.
  •  Perform a risk assessment: Evaluate potential risks associated with automation, such as data security, compliance, and potential job displacement. Develop strategies to mitigate these risks and ensure a smooth transition.
  • Prioritize cost-effective and high-ROI solutions: Choose automation initiatives that offer the most value for your investment, balancing cost with potential benefits.
  •  Assemble a skilled team or leverage existing resources: Depending on the size of the organization, build an in-house team with AI and machine learning expertise, train existing employees, or partner with external consultants or vendors.
  • Establish a strong data foundation: Ensure your organization has a robust data management strategy in place, including data collection, storage, and cleansing processes.
  • Address the impact on HR: Develop a comprehensive plan that considers employee training, potential job displacement, and the integration of new roles or responsibilities resulting from automation.
  • Implement a change management strategy: Communicate the benefits of automation to employees, address potential resistance, and provide adequate training and support.
  • Pilot and scale: Test the effectiveness of automation solutions with small-scale pilot projects before implementing them across the organization, minimizing risks and ensuring suitability
  • Opt for modular and scalable solutions: Choose AI and machine learning tools that can be easily integrated with existing systems and processes, and that can grow with your busines
  • Monitor, evaluate, and adapt: Continuously assess the performance and impact of automation solutions, gather feedback, and make refinements and adjustments as needed. Stay informed about new technologies and best practices to ensure your organization remains competitive.

Embracing AI automation not only streamlines operations and improves efficiency, but it also contributes to long-term sustainability by reducing the environmental footprint of businesses. AI and machine learning can optimize resource utilization, leading to less waste and lower energy consumption. Moreover, automation can facilitate better decision-making regarding supply chain management, enabling organizations to choose environmentally responsible suppliers and adopt greener practices. In essence, by adopting automation technologies, businesses can increase their overall efficiency, reduce resource consumption, and contribute to a more sustainable future.

While advancements in technology and the pursuit of sustainability are important, it’s undeniable that financial success remains a driving force for businesses in today’s competitive landscape. AI business process automation can play a significant role in ensuring that your organization stays ahead of the curve and generates a healthy profit margin. By automating complex tasks, streamlining workflows, and improving decision-making, AI-driven automation enables businesses to operate more efficiently, reduce costs, and enhance the customer experience. As a result, companies that effectively implement AI-based automation can reap the benefits of increased profitability and a more robust market position, reinforcing the adage that, ultimately, it’s money that makes the world go round.

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