Many consider the conference we attended last month, The AI Summit, as an AI vendor exposition. Those individuals would of course be correct. But, at Trill A.I., our team of talented, AI-obsessed developers first and foremost think of The AI Summit as the gathering of AI minds.
Bringing together industries of every vertical, The AI Summit provided a chance to connect with likeminded innovators, who recognize that artificial intelligence is not just a trend or a fad; it is a future staple of business, here to stay, and has the power to change the trajectory of any industry. Those in attendance represented organizations (wherever they may be on their AI journey) who are actively making strides to sit at the forefront of technological innovation.
What exactly did we learn?
The summit was proof that all businesses are looking to answer one specific question: “How can and how should AI be implemented in my business environment?”
Whether it was conversations with executives, managing directors, or organizations in e-commerce or manufacturing, there were common threads running between all institutions of business:
- All organizations are in the midst of setting a strategy, identifying where to go in the future with AI, and understanding the limitations and hurdles that will be faced.
- Immediate, small results need to be demonstrated before AI can be implemented across the enterprise. Majority of leaders want to see how AI will influence business, but few organizations have the capital to make such a significant investment, whether that it is due to budget constraints, risk management issues, or the general difficulty in acquiring key talent and understanding the technology itself. If AI can first be tested in smaller capacities and ROI can be documented, then larger investments are destined to follow.
- Though AI adoption at some firms isn’t happening at a break-neck pace, that doesn’t mean it’s not happening. Many businesses are deploying AI technology to improve the customer service and lead-generation process. The results give customers a more realistic, humanlike experience through chat simulations, and allow businesses to collect more data and more qualified leads.
What we didn’t see at the AI Summit
Though AI is popularly being implemented to enhance the customer engagement process, we didn’t hear of many organizations using AI to augment internal decision making or augment existing product lines. Here’s our thoughts on why that level of work has yet to be fully explored:
- Organizations are cognizant of how difficult this work actually is. The technology behind AI decision making and machine learning cannot succeed without the right people in place, but to find the right people, organizations have to put in the grueling work of identifying talent and building teams to actually make the solutions beneficial to business. Many companies rely on outside solutions to drive critical decision science.
- There still remains a strong sense of skepticism. Leaders understand building a true end-to-end AI solution (one that properly integrates new data, cleans it up, pre-processes it, and structures the problem correctly) can take years, causing many to be hesitant to make the initial investment in critical business departments. It can also be difficult to integrate into current processes. Outside vendors and consultants need to be vetted thoroughly before a relationship can be solidified.
- For most businesses, pockets of AI are spread out and don’t communicate in a unified manner. That disconnect makes it difficult to implement solutions for the collective enterprise. Often times key leadership is limited on bandwidth and has multiple priorities they have to address across multiple business departments.
Will we be back at The AI Summit this year? You bet.
The summit was an illuminating and inspiring experience. It was a reminder that some businesses are well on their way to large-scale, AI adoption, while others are in more nascent stages, and everyone is looking for partners who can support and propel them forward. No matter a business’s stage, everyone sees the value and need for solutions that can help augment products, improve productivity and drive efficiency. Fortunately, Trill A.I. is in the business of doing exactly that – improving the decision-making process for financial professionals, which leads to higher levels of performance.