An Interview With Kieran Powell
How important is emotional intelligence and empathy for the task? For tasks that involve interacting with people, such as customer service or sales, leaders should consider the importance of empathy and emotional intelligence. In scenarios where understanding and responding to human emotions are critical, humans may be more effective than AI.
As artificial intelligence (AI) continues to advance and integrate into various aspects of business, decision-makers at the highest levels face the complex task of determining where AI can be most effectively utilized and where the human touch remains irreplaceable. This series seeks to explore the nuanced decisions made by C-Suite executives regarding the implementation of AI in their operations. As part of this series, we had the pleasure of interviewing Dean Shu.
Dean Shu is the CEO and co-founder of Arphie, a software platform that uses AI and proprietary business data to build thoughtful, accurate RFP answers. Dean started Arphie after personally seeing ways that AI could transform processes as the GM and Product Leader of Studio at Scale AI, an AI leader in Silicon Valley working with companies like Open AI, Microsoft, and the US Department of Defense. Prior to Scale AI, he worked with software businesses at Insight Partners, and as a management consultant at McKinsey & Company. Dean received his B.A. in Economics and Psychology at Harvard University.
Thank you so much for your time! I know that you are a very busy person. Our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
I’ve always been fascinated by how technology can be a force for good, improving the lives of people who are able to leverage it to its fullest extent. One of my favorite quotes is Arthur C. Clarke’s “Any sufficiently advanced technology is indistinguishable from magic.”
Even during my undergraduate studies at Harvard University, I wanted to understand how technology could affect the world of business, so I sought a mix of economics, psychology, and computer science classes. I then worked at a variety of technology firms and management consultancies like McKinsey & Company, where I served technology and fintech clients on problems centered in growth and strategy.
I was excited to work with even earlier stage technology businesses, so I joined Insight Partners to evaluate whether certain business-to-business (B2B) software companies would be good assets to the portfolio. Post-investment, I worked with portfolio companies to maximize their growth and realize their full potential.
At Insight, I found the growth and potential in specifically AI fascinating. I wanted to get closer to the AI revolution that was underway, and I joined Scale AI as an early employee. Scale is an incredible, frontier-pushing company that works with all the AI innovators, ranging from autonomous vehicle companies, to various divisions in the US Department of Defense, to the most cutting-edge tech companies in Silicon Valley. During the 4 years I was at Scale, the company grew to be over 800 people, and I served as the general manager (GM) as one of our business units.
It was in this role that I gained an appreciation and insight of how AI had the potential to transform a lot of the work I was doing manually. When I left Scale in 2023, I knew I wanted to start a company that was at the intersection of the latest developments in Generative AI (GenAI) and improving sales workflows. This is how Arphie was born.
It has been said that our mistakes can be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?
As a management consultant at McKinsey & Company, we would travel weekly to work with our clients and colleagues from all over the United States. A senior partner jokingly told me that folks who didn’t miss a few flights a month were spending too much time at the airport. I took her advice too seriously. After missing a few flights in a row (including an international one for vacation), I have since re-calibrated my approach to airport arrival timing targets, and missing flights is now thankfully a once-a-year occurrence only.
Are you working on any exciting new projects now? How do you think that will help people?
We’re currently focused on building cutting-edge AI software at Arphie and serving our increasing customer base. Our mission is to thoughtfully apply AI to the problems that sales, engineering, and product teams face.
Arphie’s first product is to streamline the process of responding to RFP (request for proposal), proposals, and questionnaires. For context, businesses that buy from other businesses frequently issue an RFP to ensure they are buying the best possible product or service at the best possible price. These RFPs tend to consist of many questions, sometimes spanning into the hundreds or even thousands, and take significant time and effort to respond to.
I personally remember spending many nights and weekends on responding to RFPs for the product that I led at Scale, including a 400-question monster of a RFP that went into excruciating detail on product functionality, security posture, and more.
Unfortunately, as we talk with teams that work on RFPs and proposals, this is a frustratingly common and universal experience. However, we’ve seen Arphie give back an incredible amount of time to teams, allowing them to focus on higher-value, strategic work that moves company efforts forward, which is extremely exciting to see.
Thank you for that. Let’s now shift to the central focus of our discussion. In your experience, what have been the most challenging aspects of integrating AI into your business operations, and how have you balanced these with the need to preserve human-centric roles?
From the perspective of the customers we work with, there is sometimes a disconnect between what senior leaders believe AI can — and should — do, versus what it can actually do. We’ve also seen situations of a blind mandate from senior leaders to “use AI”, worried about falling behind in technology arms race with competitors, even when AI may not be suited for the problem at hand.
For the teams that are using the AI software we’re developing, we sometimes hear implicit or explicit concerns that the AI is there to “replace” them or take their jobs. However, we make it clear to both the teams and senior leadership that AI cannot replace human ingenuity, salesmanship, relationship-building capabilities, and more, and that our mission is to use AI as a tool to allow them to focus on higher-value, strategic work — ultimately growing the business and driving more revenue.
Can you share a specific instance where AI initially seemed like the optimal solution but ultimately proved less effective than human intervention? What did this experience teach you about the limitations of AI in your field?
We actually see this quite commonly from other companies that are applying Generative AI technology to respond to RFPs. They pitch senior leadership that their software will replace proposal teams (in part or entirety), and teams are let go based on this false promise — only for the leaders to discover that AI is not a true replacement, revenue to be jeopardized, and for the team to be hastily hired back.
The analogy I like to use is that AI is a tool like the ballpoint pen or a typewriter. A pen will not start producing thoughts and writing on its own; nor will a typewriter. To wield AI as a tool, human ingenuity and salesmanship must be infused with the AI. Similar to writing on a typewriter versus a pen, using AI can speed up the process, but there is still thought and planning that is necessary to maximize answer quality.
How do you navigate the ethical implications of implementing AI in your company, especially concerning potential job displacement and ensuring ethical AI usage?
The teams that are correctly and optimally implementing AI to streamline RFP responses should see essentially no job displacement. However, the nature of the job should change — for the better. Only the shorter-sighted teams would use AI-powered RFP software to eliminate roles and save money.
For example, at some companies, responding to RFPs is only part of the job. This is typical at B2B SaaS companies where sales engineers or solution consultants are primarily responsible for technical aspects of the “Presales” process, such as setting up and running demos, interfacing with the customer, and filling out RFPs and proposals. In these cases, using AI to streamline the RFP process will free them up from the more mundane tasks of writing or copy-and-pasting RFP responses, and instead allow them to focus on more revenue-generating activities such as doing more demos for customers, preparing for prospect conversations, and more.
At other companies where responding to RFPs and proposals are the primary role, teams spend the time saved by using AI to improve the win rate by further tailoring responses for the prospect, improve the strategy of organizing content and keeping information up-to-date, or even completing more RFPs that were previously left on the table.
Could you describe a successful instance in your company where AI and human skills were synergistically combined to achieve a result that neither could have accomplished alone?
Essentially, all the processes of Arphie’s platform require the interweaving between human skills and AI. Our philosophy is that AI is a force multiplier for human skills and intelligence — without the human component, there is nothing to multiply.
For example, after we use AI to “shred” (parse out the relevant requirements) an RFP, we provide a first-draft output of the requirements using our AI engine, and ask for human review and validation, as well as a chance to add other requirements. Our AI engine then writes a first draft to address each requirement, and loop in the team to review the responses and validate, but augmented with tools such as an AI confidence score, and the exact sources that were used to write the response.
This is because we know that trust is the cornerstone of the AI and human synergy. As people play with tools like ChatGPT, they quickly realize that AI tends to “hallucinate” — make up facts. We’ve learned that the best way to get people comfortable with AI as a tool is show the work, and eliminate the black-box problem.
Based on your experience and success, what are the “5 Things To Keep in Mind When Deciding Where to Use AI and Where to Rely Only on Humans, and Why?” How have these 5 things impacted your work or your career?
First of all, there will rarely be situations where the optimal outcome is binary — complete reliance on AI, or complete reliance on humans. We are moving towards a world where AI will be a tool for business processes, similar to how the personal computer transformed the way the business world is run.
Instead, what we coach leaders on is to understand where on the spectrum certain processes will lie on reliance on AI vs. humans intelligence.
The framework that we encourage leaders to determine the right place on that spectrum involves reflection on the following questions:
1 . What is the business objective? Is the goal of the project to increase revenue, eliminate certain types of costs, or something else? Having a clear “north star” is critical to frame the project and avoid being caught up in the “AI hype”.
2 . Is creativity and innovation a key component of the process? If the task requires original thinking, creativity, or generating novel ideas, leaders need to determine whether AI can support this process effectively or if it would be better to rely on human creativity. AI can often augment human creativity but may not be the best choice for tasks requiring original innovation.
3. How important is emotional intelligence and empathy for the task? For tasks that involve interacting with people, such as customer service or sales, leaders should consider the importance of empathy and emotional intelligence. In scenarios where understanding and responding to human emotions are critical, humans may be more effective than AI.
4 . Can the AI system adapt to new information or changes in the environment as effectively as a human? AI still needs significant amount of data and training in order to adapt to different situations. While AI can excel in stable environments with large datasets, humans are often better at adapting to new information or unexpected changes with limited data.
5 . What is the size of the impact from deploying the technology? Is the “size of the prize” worth procuring or building the technology, and all the change management that is associated with rolling out new processes? In some cases, we’ve talked with teams that complete a handful of RFPs and proposals a year, and we advise them to focus first on process improvement while RFP volume is low, as trying to implement AI too early won’t result in as much impact.
Looking towards the future, in which areas of your business do you foresee AI making the most significant impact, and conversely, in which areas do you believe a human touch will remain indispensable?
Within the realm of RFP response management, AI will continue to improve the retrieval of fact-based information. At Arphie, we’re constantly working with our customers and prospects to understand where subject-matter experts (SMEs) such as product and engineering, marketing, legal, and security teams store their latest documents. While Arphie’s ability to parse this unstructured information and extract the relevant facts for a given RFP question or requirement is already extremely impressive, our ability to unearth helpful and information from these treasure troves of data will only continue to improve. The team is staying close to the latest published research and personally experimenting with novel techniques, and we’ve already seen information retrieval and answer performance increase since we first started developing Arphie.
However, I think the human touch will remain indispensable in developing creative strategies in making RFPs resonate with customers and prospects, and increase proposal win rates. At the end of the day, a human is on the other side reading RFP responses.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂
Every day, finding 5 ways that you can make someone else’s day brighter. Whether it’s something small or large, consistently doing this will create a butterfly effect of positivity. The beauty of this is that the impact of these interactions are exponential — what you do for person X may affect person X’s interactions with A, B and C, and so on.
How can our readers further follow your work online?
We are rapidly building at Arphie — stay tuned for more product updates from us. Feel free to follow Arphie on LinkedIn, or my LinkedIn.
This was very inspiring. Thank you so much for joining us!
About The Interviewer: Kieran Powell is the EVP of Channel V Media a New York City Public Relations agency with a global network of agency partners in over 30 countries. Kieran has advised more than 150 companies in the Technology, B2B, Retail and Financial sectors. Prior to taking over business operations at Channel V Media, Kieran held roles at Merrill Lynch, PwC and Ernst & Young. Get in touch with Kieran to discuss how marketing and public relations can be leveraged to achieve concrete business goals.
C-Suite Perspectives On AI: Dean Shu Of Arphie On Where to Use AI and Where to Rely Only on Humans was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.