How to Establish a Value-Driving Intelligent Automation Strategy for Implementing Generative AI

Intelligent automation isn’t just about efficiency anymore. It’s the key to unlocking the true potential of AI and Generative AI (Gen AI) by creating applications that feel effortless, intuitive, and human-like. Today’s users crave technology that works seamlessly as a partner, not an opponent.

That’s where an intelligent automation strategy comes in. It’s not just about getting Gen AI to work better; intelligent automation is the toolset that includes Gen AI and its more about understanding what tools are available in general, and in use with your organization, and ensuring they are used appropriately, and well.

If you are looking to gain insights into the potential of Gen AI for your business, you’d love to read this blog by our resident Gen AI expert.

Recognizing Shadow Intelligent Automation (IA) Within Organizations

Most organizations are already employing various elements from the Intelligent Automation (IA) toolkit, often in what is termed ‘shadow IA’ mode.

Shadow Artificial Intelligence (AI)

Shadow AI refers to artificial intelligence applications and projects developed and deployed within an organization without explicit approval or oversight from the organization’s central IT or relevant governing bodies. This can include AI models, algorithms, or entire systems built by individual departments or employees that are not in line with the organization’s official AI strategy or compliance standards. Shadow AI can pose risks such as security vulnerabilities, inconsistent data management practices, and potential non-compliance with regulations.

Shadow IA

Shadow IA refers to the use of intelligent automation tools and technologies—like robotic process automation (RPA), machine learning (ML), and artificial intelligence (AI)—that are implemented within parts of an organization without formal approval or integration into the broader organizational infrastructure. This phenomenon occurs when departments or teams autonomously deploy automation solutions to solve immediate challenges without coordination with central IT or compliance groups. While it can lead to rapid innovation and problem-solving, shadow IA can also result in data silos, security issues, and inefficiencies due to lack of standardization and oversight.

What’s the Solution?

It’s a successful intelligent automation strategy! And it’s within your reach.

The key?
A successful intelligent automation strategy hinges on choosing the right situations for implementation. This typically involves standardizing processes or procedures to minimize variation and simplify the automation.

Let us look at a gradual and iterative approach to intelligent automation.

Establishing a Foundation for Intelligent Automation

Step 1: Establish an Intelligent Automation Office
Create an Intelligent Automation Office tasked with leading your AI strategy. This office manages resources and aligns automation goals with your company’s strategic vision, ensuring that your automation initiatives are strategic and cohesive. This office can be ‘virtual’, or staffed part-time or as required, it can also be passive (waiting for an opportunity), or active (seeking opportunities.)

Step 2: Catalog Existing AI Tools and Methods
Compile a comprehensive catalog of all automation tools and methods currently in use. This includes AI and Gen AI. This evaluation helps assess existing capabilities, spot new opportunities for automation, and eliminate redundant tools and processes, optimizing your technological assets.

Step 3: Align AI Strategy
Clearly define your business objectives and align your automation strategy with these intended outcomes. This ensures that every step of your automation strategy is purposeful and contributes to the overall success of your organization.

Developing and Implementing the Intelligent Automation Strategy

Step 4: Define Candidate Scenarios
Identify and assess candidate scenarios within your organization that are suitable for automation. Select these scenarios based on their potential impact on business goals and the feasibility of implementation. Maintain and rank these candidates based on their level of standardization and have a consistent ‘suitability checklist’

Step 5: Select Tools and Approaches – Apply Suitability Checklist
Select and vet AI tools against a suitability checklist to ensure they meet the technical needs, business objectives, and integrate seamlessly with the established strategy. This careful selection ensures the tools employed are perfectly suited to your needs.

Step 6: Design AI Solution – Launch Pilot Projects
Design AI solutions for the chosen scenarios and launch pilot projects. These projects test and refine the technology in real-world settings, providing critical feedback and performance data to guide further development.

Step 7: Continuous Assessment and Refinement
Continuously evaluate and refine your AI initiatives, adjusting strategies as necessary based on business goals and outcomes. This ongoing assessment ensures your automation strategy remains effective and responsive to evolving business needs.

Related article: Unleashing the Power of Hyperautomation: A Deep Dive into AI-Infused ServiceNow Capabilities

Partner with Advance Solutions (ADVANCE)- A Leading Elite ServiceNow Partner

Organizations aiming to implement automation solutions require a methodical and step-by-step approach. At ADVANCE Solutions (ADVANCE), we are committed to guiding you at every phase of this journey. Our deep expertise in intelligent automation equips businesses to deploy cutting-edge solutions confidently. With customized solutions and strategic support, we empower organizations to efficiently reach their objectives and fully leverage the capabilities of technological advancements like Generative AI.

Connect with us today to discuss how we can help you develop a tailored strategy that transforms your operations, achieves remarkable results, and drives significant value for your business. You can also click here to explore our Gen AI expertise.

This blog article incorporates elements and insights derived from the USMBOK™ (Universal Service Management Body of Knowledge).