Intelligent Automation: Creating the Workforce of The Future
June 7 | San Francisco
Executives spanning diverse industries met in San Francisco on June 7th to discuss the role that automation plays with their respective brands. From streamlining processes to gearing up for AI that is focused on doing good, these executives broke down how they see the future of their workforce given the current and expected trajectory of intelligent automation.
- Elena Fersman, Vice President and Head of Global AI Accelerator, Ericsson
- Datta Junnarkar, Chief Information Officer – Maritime, Boeing
- Dr. Paul Kim, Associate Dean & Chief Technology Officer, Graduate School of Education, Stanford University
- Madhu Kochar, Vice President, Product Development, IBM Automation
- Janet Lee, Chief Information Officer & Chief Digital Officer, Chevron Shipping Company
- Jared Michalec, Vice President, Client Services, Salient Process
- Hugo Perozo, Automation Leader, West National Market, IBM
- Dr. Nashlie Sephus, Machine Learning Technology Evangelist, Amazon AI, AWS
- Janice Tse, Senior Director of Data Science, PayPal
- Rajkumar Venkat, Vice President of Technology & Head of Enterprise AI, Data, Analytics & Application Platforms, Williams-Sonoma Inc.
- Avery Worthing-Jones, Senior Vice President & Head of Product Management, Gap Inc.
- Raj Yavatkar, Chief Technology Officer, Juniper Networks
- Mandeep Singh, TMT Team Lead & Senior Analyst & Host, “Tech Disruptors,” Bloomberg Intelligence
- Janet Wu, Anchor & Reporter, Bloomberg
Preparing a New Wave of AI Specialists
When it comes to the question of whether we’re producing enough AI leaders for the future, the answer was more somber than optimistic. Dr. Paul Kim, Associate Dean & Chief Technology Officer, Graduate School of Education, Stanford University, says no – absolutely not. At least not from his perspective at an institution tasked with creating the next wave of capable intellects, and it’s a problem Stanford University is working on tackling.
Those who create AI are unique leaders who need to understand both the knowledge and know-how behind the building, but also the creativity and problem-solving skills to make a product seamless – especially for large industries. Some of these qualities are not assessable with traditional tests and require new learning environments and new learning goals. Things are headed in the right direction, but to build the best future, we need the best leaders, something that institutions like Stanford are working on creating. Datta Junnarkar, Chief Information Officer – Maritime, Boeing is also seeing a similar push in the community college space as more institutions fight to keep up with demand.
Difficulties to Automate in Different Sectors
Not all industries are as eager to move into an automated structure, and some are downright restricted in doing so. Janet Lee, Chief Information Officer & Chief Digital Officer, Chevron Shipping Company, explains that the maritime space is slow to change because it is steeped in thousands of years of tradition. The universal standard is older, manual methods because of this. While a primarily virtual shopping brand in Silicon Valley could easily automate much of their processes with few regulations, technology that is applied to ships is subject to international laws and other standards, creating cultural barriers that are nearly impossible for some to mount.
Similarly, Madhu Kochar, Vice President, Product Development, IBM Automation, makes the case that there is a difference in AI between Alexa and implementing it in enterprises like airlines that run the world. How do you train newcomers, and what does it take to deploy AI solutions in these situations? It’s not a matter of just creating a helpful home device. It is interrupting and rewriting industries that are largely reliant on people, their interactions, and respective duties within their line of work.
Automation is Not Always the Answer (At Least Not Right Away)
Despite the buzz, automating or implementing AI is not the solution to every business challenge. There are a million reasons why a company may want to use AI, one being that the volume of data cannot be processed in any other way but machines, concedes Raj Yavatkar, Chief Technology Officer, Juniper Networks, but it’s not always the first step.
This is something that Jared Michalec, Vice President, Client Services, Salient Process, has seen in his work with clients. Too many organizations have misguided hopes of jumping into AI when they’re in the beginning stages of digitizing their processes. Rather than jumping into the latest tech, the change is a process, and one that begins with getting online, modernizing the parts of a business that need to be first.
Once a company is strategically transitioned to higher technology, benefits like a pseudo-world can be used to help improve accessibility for both newcomers and seniors for consistent training, brings up Hugo Perozo, Automation Leader, West National Market, IBM. This is something that Avery Worthing-Jones, Senior Vice President & Head of Product Management, Gap Inc., experienced firsthand during the pandemic when something as simple as store walk-throughs went digital to accommodate a world that had largely shut down.
AI and Sustainability
As the conversation on automation veered into the topic of nonfungible tokens (NFTs) and the longevity behind high-tech, Rajkumar Venkat, Vice President of Technology & Head of Enterprise AI, Data, Analytics & Application Platforms, Williams-Sonoma Inc., explained what a growing portion of Williams-Sonoma’s client base is looking for in their products: sustainability. Younger generations like millennials and Gen Z are trending more toward supporting causes they care about than the price point. Venkat goes on to explain that this is not a fad and instead something that a large demographic of William-Sonoma consumers care about.
So how does that fit into AI? The question of whether high-level tech is justifiable given the sheer amount of power it takes to keep running is a reoccurring one. For brands that want to meet their consumer demands for sustainable business approaches, it’s an important one to consider. Is the benefit of implementing AI worth the potential cost of setting up and implementing those systems, especially when working within a set sustainable budget, as mentioned by Venkat of Williams-Sonoma Inc.
Lee of Chevron Shipping Company says it’s not always possible. There are different strategies depending on the economy and location. While there are some consumers and workforce interested in causes like sustainability, not all locations have the luxury of choice.
Another area where sustainability comes into play? Human rights. Gap’s Worthing-Jones chimes in with an emphasis on how sustainability is more than high-tech and blockchain, it’s the people involved – the ones that can get left behind in tech-led conversations. As new tech evolves and things are automated, it’s crucial that humans remain at the forefront of that discussion. Human rights violations are all too common within factory settings, especially fast fashion. How do we build AI that does good for the world, rather than push good away?
A Focus on Ethical AI
Rounding out the conversation on all that AI and automation could do in the workforce, most executives settled on one goal: high ethics. Elena Fersman, Vice President and Head of Global AI Accelerator, Ericsson, hopes that one day more data could be opened up for innovation, such as data-sharing between universities and corporations with a common goal of innovating for the future.
Dr. Nashlie Sephus, Machine Learning Technology Evangelist, Amazon AI, AWS, agrees that she would like to see more responsible AI being deployed so we can move more toward inclusivity. AI can be used to solve all of the problems in the world, and we have the data and means to do so, says Janice Tse, Senior Director of Data Science, PayPal.
On a parting note, “Use AI for good,” says IBM Automation’s Kochar. “Ethics matter.”
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