5 Guiding Principles on Operationalizing AI for Success
Updated: Jul 8, 2021
This article is part of Seleya's blog series "Investment Research: Time For Innovation".
Implementing AI into organizations is an innovation and change management exercise. Based on our experience of operationalizing AI into other investment platforms, we offer guideposts that foster internal alignment and clarity.
#1 Strategic, Not Tactical
Companies start off enthusiastically as they embark on their AI ambitions. When it comes to executing on the vision, the typical corporate playbook is to deliver “quick wins” ideated at the grassroots level. Yet, these point solutions tend to have low ROI, impacting only a few, and corporate enthusiasm quickly wanes.
In contrast, successful companies strategically deploy technologies with broader impact. The extremely successful have deployed technologies that amplify the organization’s competitive strengths. As an analogy, “if you needed to digitalize your HR system, would you piece together many tactical tools; or, would you implement a comprehensive solution like Workday?”
#2 Measuring Objectives
The most common mistake is to measure your AI initiative's success purely on alpha-dollars generated. AI can enhance your organization's effectiveness and improve your investment research. As an analogy, “how do you measure the ROI of Bloomberg terminals?”
#3 Focus on Common Elements
Identifying common pain points across investment teams requires an enterprise perspective and investment domain expertise. The payoff is better ROI, scalability, and usage. The investment research process stands to benefit the most from innovation across asset classes.
#4 Proprietary Data vs. Alternative Data
Investors can be tempted to buy “exotic” data such as credit card spend or satellite imagery. However, such datasets are expensive, noisy, resource-intensive, and limited re-usability. We have found internal proprietary data to be much more valuable with higher ROI potential.
#5 Competitive Differentiation
Many vendors offer point solutions whose information value decays rapidly and lack proprietary insights. Yet every organization needs an AI platform that is unique to their organization with sustainable differentiation.
How do you implement an AI platform that is impactful, differentiated and generates high ROI? Seleya Technologies has been authoring the intersection of AI and investing since 2013. Use Seleya's Expert^AI to scale up the number of your high-quality investment ideas and enhance your information advantage.
Contact us at firstname.lastname@example.org to learn more about Expert^AI and our enterprise solution. We look forward to working with you.
Seleya Technologies is an industry expert in AI and quantitative analytical tools for financial institutions. We leverage AI to augment human perspectives, enabling financial institutions to make decisions faster, more accurately, and with less bias.
Our two solutions include ExpertAI for institutional investors and ExpertAI ESG™ that scales up a financial institution’s in-house, proprietary ESG assessments.
Our team has been authoring the intersection of AI and investing since 2013. The company is founded by experienced investors and computer scientists with over 20 years of experience developing solutions for financial institutions.