Keeping pace with regulation: Metering societal and ethical impacts of innovation

Environmental and social governance (ESG) is not only an ethical responsibility of organizations, but also a legally mandated one, particularly as it relates to AI use, data ownership, and other privacy-related issues. While the c-suite might initially see this as added liability, the increasing maturity of AI is yielding standard industry practices with regulatory compliance in mind.

Large sets of enterprises are increasingly adopting intelligent automation frameworks that reflect a commitment to preventing or reducing negative environmental and social consequences of innovation. Moreover, most regulatory policies related to AI are still in the process of being formalized and are not yet enforceable, meaning enterprises have time to ensure that their applications of AI are entirely ethical and compliant. One strategy for ensuring compliance is championing an advocate for ethical artificial intelligence within your organization. ABBYY, for example, is supported by AI Ethics Evangelist Andrew Pery, who is an expert in trustworthy AI and AI bias. Pery helps customers and clients understand how data is being shared, what it’s used for, and how ABBYY ensures transparency, fairness, and privacy. Providing a platform to professionals in this facet of artificial intelligence conveys to stakeholders that ethics and responsibility are taken seriously.

Automating with intention: Understanding your organization’s needs

Implementing intelligent automation can be a daunting task. It’s a significant investment of time, money, and other resources, and it can be ambiguous as to whether an automation initiative will succeed or not. However, IT leaders can drastically improve their odds with clear goal-setting and high visibility into their processes—after all, most automation goals fail due to unclear goals.

Every process, enterprise, and industry have their own nuances. It’s important to understand how and where you’re starting your automation journey, and why you’re doing it in the first place. Breaking it down helps to comprehend business, corporate, and technological processes, which is a key step towards scalability. IT leaders should ask: “How are we automating across a broad set of processes rather than one part of a portfolio? Then, how do we recreate it?”

Using an AI-enhanced tool like process intelligence gives enterprises the visibility they need to cultivate this thorough understanding of their operations. From there, decision makers can make informed decisions and test process improvements before implementation, reducing the risk of wasting innovation budget on a failed automation attempt.

Maximizing your investment: Best practices

Making a sustainable investment in automation requires thorough understanding of customer segments. Consider the expectations of every stakeholder and every office in an enterprise, as well as the deliverables, objectives, and other points of interest for every office. Taking input from all c-levels establishes more sensible automation, and thus supports sustainability.

Ashwin believes that enterprises have graduated from the concept of a “center of excellence,” moving instead towards a “center of value.” We should start thinking about how value is generated and delivered to our whole ecosystem, beyond just customers. Centers of excellence are purely technical, trying to deliver outcomes—but centers of value are more focused on making an impact on both internal and external entities.

A center of value should strive to establish a scalable roadmap that considers multi-dimensional integration. This leads to the connection and collaboration of various entities and attributes, reminding decision makers of competitive position, status, and maturity.

It is also imperative to use the right framework consistently across all automation solutions used by an organization, and to consider the lifespan of automation cycles; or, how long an automation cycle can operate without disruption. Metrics like these will allow automation initiatives to be further measured and optimized accordingly, ensuring you get the most out of your investment.

Communicating these priorities and establishing a clear roadmap towards operational excellence through intelligent automation is an essential step to garnering executive support for such initiatives.

Tips for driving executive buy-in

There are many factors to consider when considering or proposing an automation strategy, but IT professionals can identify certain key aspects when pursuing executive buy-in:

• Show the end-to-end scope of automation and its overall impact on specific use cases
• Articulate the technology elevation that impacts stakeholders’ experiences and gains a more competitive market position
• Showcase domain and function-specific enhancements, such as in ESG
• Provide peer references from industry verticals; both within your vertical and adjacent ones
• Present a readiness roadmap that illustrates the timeline from implementation to value

For conveying the end-to-end scope of automation, focus most on how work methods and processes are being elevated beyond automation. It’s crucial to highlight how the technology transforms entire industry practices, and it is necessary to keep up with the pace of innovation. Also, focus on the solution scale across verticals, as communicating the cross-pollination effect is a tantalizing point of value to executive management. The roadmap can consider quantitative benchmarks that provide higher visibility into ROI translation, making the value appear as tangible as possible.

The speed of innovation shows no signs of slowing. If decision makers are to keep their organizations up with the pace, it’s crucial for them to understand the value of intelligent automation, and ultimately see to its implementation.

My conversation with Ashwin was an illuminating illustration of just how powerful intelligent automation can be for businesses if approached, adopted, and implemented in the right way. Our Q&A session with live attendees further delved into the nuance of company cultures and tech stack logistics. If you’re looking to gain further insight into making the business case for intelligent automation, you can watch the full webinar recording here.