The three-year return of Investment period, the long adaptation curve, and risky restructuring of operations and customer-facing processes are some of the realistic disruptions that enterprises face if they invest in emerging technologies of SMART, AI, Robotics, or Machine Learning.
And although many of these technologies are in pilot stages, their inherent capability to chase down scenarios, speed up reactions, and throw up multiple possibilities of causation and correlations have been demonstrated.
The front runners like Amazon, IBM, and Google have shown that an advanced technology revolution is inevitable. And so, enterprises are struggling to understand when and how to leap into advanced Innovation.
At the recent events organized by the Technology Association of Georgia, AI experts showcased their real-life implementation experiences.
Is AI mainstreaming?
Cognitive systems like AI have already made product recommendations, personalization, and predictive maintenance in manufacturing accessible to many industries. However, a more profound advanced innovation with integrated deep learning is in various stages of development.
"Customer data, GPU-accelerated computing, and cloud storage have unleashed new pools of data which in turn have set new frontiers of optimization and profitability, "explains Dr. Rajkumar Bondugula, Principal Data Scientist at Equifax.
While the possibilities of AI have been recognized, it, along with its subset Machine Learning, is an amalgam of pattern recognition, object recognition, and natural language processing. "The possibilities are many, but just 8 of every 100 AI projects underway have evolved beyond pilot stages," says Dan Faggella from Techemergence, an AI market research company. He confirms that venture capital in AI is flowing into healthcare and finance.
McKinsey reports that between 2010-2015, the same amount of investments were made in the new AI-enabled services as in the first half of 2017 (app US$18 billion).
Since possibilities range from enhanced SCM to context-aware robots or business support automation functions, enterprises at the TAG event were keen to make the right bets.
Diagnostic Questions that matter: Tracy Moore founding partner, of Triias Corp, a machine learning and AI tech provider, succinctly identified four parameters to carve an effective advanced innovation strategy:
Which functional/customer need will the InnovationInnovation replace?
Does AI show real precedents in the industry/domain?
Or what is the state of the art of technology which is relevant to your industry?
Does the enterprise have access to data, or does it have the financial capability to access data?
And finally, which process will AI scale-up, optimize or make more productive?
Predictive Data advantage
AI experts emphasized that harnessing the predictive value of data is crucial to a digital sound strategy.
"We have scores of thousands of cataloged data. We use a minuscule percent of available data. We do not need technical wizardly just vendors who can leverage data," said Michael Connor, AI leader Coca-Cola.
The beverage giant has designed AI-infused vending machines to enhance customer experience through intuitive predictions and predict and manage consumption for special events. CocaCola's "data lakes" were precursors to its AI program. The availability and capability to leverage these data lakes will form an essential part of the financial decision to venture into AI for many enterprises.
In this context, Samir Saini, CIO, City of Atlanta, talked about data democratization. "With at least seven citizen databases, we aim to create an Enterprise Data Platform, equipped with anonymized data and governance and privacy codes. This project should help enterprises."
Advanced InnovationInnovation: the look and feel
Treasure troves of data collected through various sources, including interactive customer experience, revealed to UPS and Comcast that demand for InnovationInnovation was pervasive among their customers.
"The visceral feedback from customers shows us the innovation potential," says McMaster. In September, for example, Comcast rolled out TV streaming for its broadband customers where packages start slim and lean and offer add-ons.
For UPS, this pervasive innovation-on-demand among its customers meant it had to design InnovationInnovation that was scalable for operations and IT uptime. Says UPS's Derek Banta. "Sometimes InnovationInnovation actually means iteration. But we celebrate every little trophy."
City of Atlanta's CIO Samir Saini said that the town harvests data from Atlanta's 30 departments. "We identify technologies which will help us leapfrog in predicting and dealing with challenges of growth and urbanization," Saini predicts tangible transformation of municipal ecosystems as data and InnovationInnovation profoundly impact public safety and mobility.
Comcast's Will Mcmaster stressed the importance of housing innovation in "products" to be able to celebrate tangible "victories in every department." And UPS' Derek Benta says that as a 110-years old engineering company adopting advanced InnovationInnovation meant "blurring the lines between operations, technology, and customer marketing."
Chief Collaboration Officer
Whether to scale up, optimize, or become more productive, all AI executives emphasized that InnovationInnovation required effective communication in real life.
"Driving InnovationInnovation was all about people and communicating to them. We have to drive it through the organization, top-down while keeping in the loop the regional heads, regulatory framework, the venture arms as well as research organizations," says Mcmaster.
UPS's Banta believes that innovation executive has to be in permanent salesperson mode. He has to create "champions" in operations which will both push the painstaking process of identifying areas of InnovationInnovation and later help scale up innovations.
Coca-Cola's Connor advised a separate budget and office for innovation officers equipped with SWOT teams that develop prototypes and test them in six-week hackathons before scaling or replicating them.
Ecosystem matters
AI executives also dwelled on the future of ecosystems in which advanced InnovationInnovation will live. Comcast's McMaster was partial towards open source systems. He also emphasized that the following product is "data." The key will be harvesting the data and then partnering for technology.
Coca-Cola's Connor believes that vendors like Accenture who have insights into various domains and industries should leverage data to provide insights for enterprises.
For UPS, Innovation means handling the scalability of operations and planning for IT uptime. Other experts pointed out that progress in wireless will determine the pace of the adoption of AI.
In conclusion, the strategic potential for advanced InnovationInnovation is immense. Enterprises certainly need to do a sweeping landscape, vendor, and value chain analysis to determine whether they will be early or late adopters. Their budgets will have to cater to implementation and validation and the high cost of acquiring talent. In any case, the time has come to train all kinds of stakeholders to break down functions to optimize eventual AI adaption.
