In recent years, discussions surrounding the next stage of decision intelligence have been heating up, with an increasing number of businesses finding dashboards as a form of information and source of insights greatly saturated in value. The emergence and growth of large language models (LLMs) over a year ago provided a significant technological breakthrough, and many BI tools now come with an NLQ / GPT layer. However, it is still unlikely to provide the value enterprises look for when making decisions.
Rethinking business needs, rather than retrofitting new technologies on existing tools
Given the opportunity with LLMs and the traditional backlog of issues with traditional reporting tools, it is time to rethink business teams’ needs and build a new layer of “Modern Intelligence” that addresses them.
Converging information for better decisions
In the realm of knowledge work, possessing the ability to make informed decisions is highly valued, but the issue is that these decisions are often based on incomplete or missing information. It’s not the sheer volume of content produced or dashboards to implement or justify these decisions that matter, but the quality. Today, the business lives in a highly distributed world where dashboards shed light on performance data, some other analysis dives into why and how. For competitive intelligence, the best tools are still somewhat better versions of Google Alerts.
One goal of future-proof tools, aka Modern Intelligence, will be to enable a blend of synthesis and analysis, regardless of data type, to elevate the quality and speed of decision-making processes. A prime example of Modern Intelligence is its potential to leverage LLMs to condense vast amounts of data that would be overwhelming for humans to process themselves.
Simplifying information & UI
Most business intelligence tools in the market today were not designed with a decision intelligence framework in mind. Gartner recently estimated that less than 10% of analytics and business intelligence tools have a decision-centric UI to model and track decisions. The consequence is that the majority of business teams are not able to action information as it’s not specific or simple enough. Consumer internet applications provide some ideas about how UIs and information can be simplified.
For example, Orange Theory sends a workout summary through email after every workout, and The Medium sends a curated list of the most relevant articles for users to explore. Both of these examples show how simplified and targeted information can help users make an informed decision (the Orange Theory member could see their workout summary and decide actions for next workout, and the Medium reader receives a highly curated list they are interested in).
The future significance of Modern Intelligence will lie in its capacity to assist humans in making smarter, quicker decisions. In some instances, It might even extend to making decisions outright.
Being at the right time and right place
Hidden or inaccessible data has been a recurring business complaint for many, especially when there is little time to read long reports or dig through a series of dashboards to answer a question or make a decision. While this is partially a data science problem, the main issue stems from a behavioral science problem.
Modern Intelligence will be able to provide ”unprompted intelligence” that highlights the most relevant data & insights (reducing time spent), make reports simple and intuitive (increasing engagement), and proactively push personalized insights to users (customized experiences).
Applying Modern intelligence as the new decision layer for enterprises
So, if we think of Modern Intelligence as an AI-powered decision layer for the business, it can unlock significant value for enterprises. Below are some applications for Modern Intelligence:
| Function | Current Scenario | Future with Modern Intelligence |
| Competitive Intelligence | Google Alerts and Syndicated/bespoke competitor reports | Automated monitoring & analysis of financial, web, earnings, CRM, etc., to provide key insights on strategies and plans |
| Content Marketing | Content topics, production, and SEO are largely based on experience and high-level client needs | Blended analysis of internal data (CRM) and external data (news, feeds, etc.) to identify relevant topics and insights |
| Sales | Dashboard-based performance reporting | Nudge-based intelligence personalized to your pipeline, client focus, and opportunities |
| Product | Generate specs and prioritize roadmap based on internal methods | Real-time intelligence on client needs based on CRM interactions and feature prioritization based on revenue opportunity |
| Customer Service | Dashboard to track open tickets | Real-time alerts to prioritize tickets based on decision models that incorporate various CX considerations |
| CXO | Ask 5 people for an update on 10 KPIs | Receive updates on important KPIs in your inbox every week |
| Financial Analyst / IR | Spend 2-4 hours analyzing quarterly statements and transcripts of a company | Summarized contextual insights available at the click of a button |
In general, use cases that make the most of Modern Intelligence will be where there is:
- A high volume of information makes it difficult to manually aggregate or sift through it. For example, reviewing earnings transcripts, sifting through data/dashboards across the martech stack, or reading detailed analysis.
- A high value factor where noise can be reduced for people looking at specific kinds of information for a specific purpose. For example., revenue opportunities for sales teams, cost reductions for service delivery teams, and/or risk mitigation for operation teams.
About Bloom AI
Bloom AI is a modern intelligence layer for enabling data-driven decisions. We empower enterprises to unlock the value of data with human-like synthesis and decision intelligence at scale. Our proprietary tools and solutions are trusted by investment managers, insurance, private equity, and Fortune 1000 companies for more informed, efficient, and productive business practices. We are located in Raleigh-Durham (U.S.) and New Delhi (India).
