The Holy Grail: The quest for achieving end-to-end AI

While the results are evident, struggles to scale AI, and thus its returns, remain. According to reportsiv over 70% of companies find it difficult to scale AI, most only able to implement it piecemeal. Large scale adoption challenges leave AI projects in fragmented silos across the business affecting ROI. This is a result of viewing AI as just another technology implementation and not something that requires organizational change.

According to BCGv , companies that make extensive changes to many processes for AI adoption are 5x more likely to realize significant financial gains. A glimpse of this transformation is visible to those few who have managed to scale AI across processes and departments to get closer to the end-to-end AI vision.

For instance, a leading O&G player has been able to use AI across its operations to prevent equipment malfunctions, reduce maintenance costs, and scout for new oil & gas deposits 80% faster. Another great example of this is the contactless Amazon Go storevi where customers just walk in the store, pick up the items they need, and walk out without any checkout or waiting. At Edgeverve we’ve helped companies across the board weather the pandemic with AI interventions. For example, a leading bank was able to process 25,000 PPP loan applications in just a week, processing 15000 digital forms per hour; a cosmetics major was able to respond to market demand instantly with real-time promotional insights; and a healthcare manufacturer saved $40Mn in costs with end-to-end intelligent automation.

It is time for companies to start looking beyond pilot projects and focus on AI proliferation. Embedding AI in every aspect of their business can catapult their growth in the new normal. To do this they need to:

• Define a holistic AI vision
  Lack of an AI vision is the reason most AI scaling projects flounder. Companies need to define a vision and AI roadmap to deliver the specific outcomes that would make business sense for them.
• Do detailed due diligence
  Not identifying the potential challenges, right partners, and hidden costs, etc. can derail an AI project even before it begins. Take time to understand how the project would impact the organization and plan out a seamless transition from the get-go.
• Invest in data quality
  Most organizations lack the capability to provide volumes and quality of integrated data that AI systems need to perform optimally. Ensuring top-quality data would ensure AI performs as expected.
• Modernize legacy infrastructure
  To support AI at scale the rest of the IT infrastructure must also be agile and scalable, something that traditional structures lack. .
• Mitigate organizational resistance
  Be it the existing processes or unwillingness of people to adapt to the change, organizational resistance can be a big deterrent for AI implementation. It’s very important to get stakeholder buy-in and put in place internal communication campaigns to make a cultural shift.
• Build AI-related skills and competencies
  Upskilling existing resources and creating new technology partnerships must be a high priority.

Dawn of a new era

The shock of COVID-19 will be felt in the years to come. However, there is an opportunity in every adversity. In the aftermath of the COVID-19 pandemic, we stand at the gateway to a new decade that is ripe for change. Depending on how we leverage the tools and technologies available to us, we can write the next chapter of business growth. In a white-water world, end-to-end AI can help companies pivot strategies and tactics in real-time. AI engines can create new synergies across the value chain increasing collaboration, boosting innovation, and taking end-user experience to new heights in a new remote world connected by technology.

While AI adoption marches full steam ahead, and investments in AI increase across the board, the most successful businesses will be those that are able to get machines and humans to work together collaboratively. The agenda in the coming decade, to solve most of the challenges businesses are plagued with, is about combining human ingenuity, creativity, and emotional intelligence with the efficiency, accuracy, and agility of artificial intelligence.

When it comes to the potential of AI, we have just scratched the surface. This is, indeed, just the beginning.

References:

1. https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-covid-19-recovery-will-be-digital-a-plan-for-the-first-90-days
2. https://www.visualcapitalist.com/every-minute-internet-2020/
3. https://www.techrepublic.com/article/ai-is-accelerating-the-move-to-a-touchless-world/
4. https://www.forbes.com/sites/gilpress/2019/11/29/63-of-executives-say-ai-leads-to-increased-revenues-and-44-report-reduced-costs/?sh=5a046efa14b3
5. https://www.bcg.com/publications/2020/is-your-company-embracing-full-potential-of-artificial-intelligence
6. https://bigdata-madesimple.com/ais-impact-on-retail-examples-of-walmart-and-amazon/