SOPs and AI Readiness

Luck Favours the Prepared

In the yesteryears, we told machines what to do; today, we tell them how to learn and then improvise their actions. This ability to learn on their own makes the intelligence of machines different from that in the past. Take the examples of autocorrect or word suggestions which are now common with search engines and email platforms. These recommendations do not seem to come from the dictionary or general popularity but are based on past search and typing behaviour. These examples are meant to show the growing capabilities of what we happily call Artificial Intelligence or AI. Things become more interesting when these capabilities are extended to other applications like improving business operations.

The use of AI in business process management has already arrived. Although this might not have yet become commonplace AI is going to go deep and wide leaving hardly any business untouched. If any references are needed to convince ourselves of this, we can recall the impact of eCommerce on traditional retail. Driving on technology, eCommerce compelled traditional retailing to change. The good side of this impending influence of AI is that organisations can prepare for it. One such vital ground of preparation is operations planning.

The objective of this blog is to showcase how Standard Operating Procedures or SOP solutions can help businesses get their operations framework ready for AI adoption. Five pictures of this phenomenon are presented in this blog.

Operational Specifications for AI Adoption

Any kind of automation including the use of AI is much more challenging in an undefined or poorly-defined operational environment. Maybe humans can get away with poor process planning but machines cannot. Machines have to be told what is to be done in certain terms. Even in the case of AI, the parameters have to be drawn. You cannot replace salaries with credit of leave days to the account of employees or you have to tell the software what the data parameters are to analyse attendance behaviour. Having robust process definitions makes it easier to identify these informational requirements and locate them. This is where SOPs chip in. SOPs require defining every process/workflow to a high degree of detail covering every operational aspect. For example, if AI is used for demand forecasting, the AI application must function and provide output in a specific manner unique to every business. The application must be told what informational inputs it must process, what/how it must learn, and what output it is expected to generate. If a business enterprise does not know how it currently measures demand, it won’t be able to tell the AI application what to do.

However, if a well-defined process (SOPs) already exists for the purpose, the same informational package and processing requirements would also apply to the AI application. AI applications may require additional information that can be later attached but the fundamental informational requirements would be already available because of having SOPs in the first place.

Adaptability of the Operations Framework

Technology keeps on evolving and this affects how businesses that use the affected technology realign their operations framework. While in ordinary cases it may not be necessary to go for the higher version of a technology, things get a little tricky with AI. It is like denying an improved way of thinking. In business, such decisions can have undesired ramifications. Suppose that your business uses an AI-powered CRM software application that gives you far more insights than any traditional analytics platform. If an upgraded version comes up and you decide to stick to the older version, your analytics may become less competitive if other players choose to move to the upgraded version. However, in deciding whether you want to upgrade the application or not, you will still need to know how to evaluate the incremental benefits of such upgrades. If you have well-defined SOPs for CRM, you would have a better chance of determining whether and how the upgraded AI capabilities could aid your business prerogatives. For instance, if the new AI capabilities say that it can now analyse data from additional sources, it will not be difficult for you to determine whether the new informational requirements are available within your process or not. This is because functioning via SOPs requires the collection of process-related information. SOPs can be modified to include such requirements. This opportunity is denied or becomes extremely difficult to capture if SOPs are not present or are not well-defined.

Focus on Results

AI requires emphasis not just on workflows but also on the results of workflows. When you are asking a machine to learn and adapt, you must also be able to provide it with crystal-clear objectives. Suppose that you want to implement an AI-powered CRM software platform. Before doing so, you must already have a clear vision of the different outputs you intend to achieve from your different CRM activities. For instance, one of the objectives of CRM is to achieve effective product recommendations. Product recommendations can be considered to be effective if customers choose to buy one or more of the suggested products. There is a process involved as to how products would be recommended and how to measure the effectiveness of that process. SOPs not only help define workflows but also lend result-orientation to those workflows. These definitions of expected process results are vital for AI applications to learn better and deliver more accurate results. From the SOPs, AI applications can identify which data fields must be analysed, and to what end the data should be processed, measure effectiveness, and find the scope of improvements in the process. Since SOPs provide the operational details to a high degree of attention, it becomes easier for AI applications to perform better and faster.

Room for AI in Operations Planning

Not all businesses might be looking at adopting AI solutions at the moment. Investments in AI solutions may not provide commercial justifications to small or even many medium-sized businesses. However, the impending influence of AI cannot be overlooked. Businesses need to keep a tab on the areas of their operations that might be affected by AI. For example, a company may have to bear the burden of a longer recruitment process than its competitors by not adopting AI and relying on higher levels of human intervention. However, making those measurements and decisions on process performance is nearly impossible if there are no process maps. If SOPs are present, it becomes easier to evaluate and compare process performance under different circumstances. In other words, assessing if there is room for AI or measuring the improvements AI could bring in the execution of business processes becomes simpler.

Change Management via SOPs

The growing popularity of Artificial Intelligence has also brought concerns about job security, the changing nature of employment opportunities, and the impact on human roles. While concerns can be diminutive at times, sometimes the reasons are pretty solid. For example, AI has proved to be superior to average human skills at data-oriented analytical tasks raising some apprehension among those in this field about losing jobs to machines. Also, AI can execute complex tasks with higher efficacy than humans. The use of AI also carries the potential to deprive scope of a rise in salaries. While at the macro level, addressing these concerns will require industry-wide efforts, at the organisation level, SOPs can help reduce apprehensions and resistance to change.

Many contemporary SOP experts often reiterate that well-crafted SOPs provide an opportunity for employees to better understand the reasoning behind the role of AI in workflows. This allows them to see AI as a facilitator in their work, a chance to diversify their expertise and not a role-snatcher. Let us try to get this with an example. Suppose that a workflow comprises the tasks – A, B, C and D. With AI adoption, C and D will now be carried out by AI. This reduces human role and possibly will also result in changes in the job description. SOPs help integrate these kinds of role transitions that may involve inclusion in new processes as well. For instance, a recruitment executive may have a lesser role to play in a recruitment process with the adoption of AI that can be compensated by assigning new responsibilities in another process, say onboarding. SOPs help employees embrace these kinds of cross-process role transitions with better clarity than mere verbal announcements.

Training for the Future

SOPs are also instrumental in designing training programs. It provides valuable inputs on operational standards and requirements that employees must adhere to when they play their parts in the execution of business processes. The future scope of the inclusion of automation and AI could be highlighted and incorporated into the training programs. This will help employees embrace AI with a prepared mindset. They will know in advance which part of their roles might one day be done by AI. This will help both employees to plan their careers and develop or acquire new skills. On the other hand, organisations will also benefit by being able to map their skill and competency requirements in the future.

Consider a recruitment training program. The incorporation of AI-powered automation in the near future will affect many areas of this recruitment process. For example, AI would keep improvising the resume screening activity over time as it will have access to more data and instructions. This will enable hiring executives to rely more confidently on automation and shift their focus to other areas where their manual expertise is more necessary. Although resume screening automation solutions are already in use, the power of AI will take it to a level where the role of human intervention in this process will significantly go down while creating the scope of a more focused application of human expertise.


AI is going to leave hardly any business or profession untouched. The use of Artificial Intelligence for improving business processes has already arrived. As experienced business process consultants, we see that SOPs can help organisations in getting their operations framework geared up for AI adoption in numerous ways. Having sound process definitions makes it easier to identify and source the operational information used by AI tools and applications. These crucial inputs provided by SOPs also help in lending agility to operation frameworks in the backdrop of rapid developments in the field of AI applications and the possible need to adapt to one. Because SOPs provide operational information with a high degree of detail, they facilitate AI applications to perform with higher efficiency and effectiveness. With SOPs, it becomes convenient to compare process performance under the use of different sets of resources. Well-crafted SOPs provide an opportunity for employees to see AI not as a role-snatcher but as a facilitator in their work and a chance to diversify their skills and competencies. SOPs also provide valuable inputs for designing process training programs wherein the scope of AI adoption could be highlighted.

To know more about our SOP consulting services or to speak to one of our SOP consultants, please drop us a message and we will reach out to you. Please visit our website to read more about our SOP design and implementation services.


SOP is the initialism (type of acronym) for Standard Operating Procedure. Think of SOP as a cooking recipe. It describes how a process needs to be carried out in a step-by-step or systematic manner leading to the intended process outcome(s). Every step in the process is also defined further with details of what needs to be done, who will do it, when it has to be done, what output is expected, and so on. Like making a cup of coffee, making a car also involves a process defined by a series of SOPs for multiple sub-processes, operations, and activities.

Here are some important KPIs for SOP development and implementation:

  1.       Defining the process significance, process objectives, desired process outcomes
  2.       As-is mapping of the existing processes and practises
  3.       Process gap analysis
  4.       Development of the new SOPs
  5.       Validation (Adjustments and improvisations during pilot/trial runs)
  6.       Identifying IT/software solutions
  7.       SOP-IT integration
  8.       Software customisation and installation

9.       SOP Training

Author Bio


Rupal Agarwal

Chief Strategy Officer
Dr. Rupal’s “Everything is possible” attitude helps achieve the impossible. Dr. Rupal Agarwal has worked with 300+ companies from various sectors, since 2012, to custom-build SOPs, push their limits and improve performance efficiency. Rupal & her team have remarkable success stories of helping companies scale 10X with business process standardization.

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