So much data is easily accessible to all of us. It takes the right tools and team to correctly analyze that knowledge and turn it into relevant insights that drive success.
AI has been the catalyst in driving data into decisions.
Let’s Talk AI
Artificial Intelligence or AI, once a futuristic concept, has become our everyday reality. From self-driving cars and cloud machine learning to illness detections and robots, we benefit from AI every day. AI can be divided into two main groups.
- Narrow AI, Narrow AI, sometimes known as “weak AI,” is the type of AI that outperforms human tasks narrowly or in a very structured manner. It often performs singular functions like internet searches and face recognition with limitations.
- General AI, also known as “strong AI,” is the AI that enables machines and processes to be applied in a variety of contexts. It is the ability of a machine to intellectually understand the world like humans. An example would be a chat box using natural language processing to respond to humans or autonomous cars.
Challenges
- The disconnect between research and outcomes: Artificial intelligence can help companies sift through data, an invaluable task because there is just way too much out there. According to Forrester, about 74% of firms say they want to be data-driven but only 29% of them successfully connect analytics to actions. Gartner has found a similar disconnect between data research and outcomes.
“While the big data sets now exist, only 20% of insights are ever baked into outcomes,” a Gartner report said.
- Sorting through to find the right kind of data: Taking copious amounts of data and turning it into insights and measurable outcomes has CI professionals stretched thin. Other challenges include finding the right, most insightful data and creating a dynamic business strategy around it.
CI teams serve all different departments in a company, whether that’s sales, marketing, procurement, or executives. Each team needs different things to be successful, and CI teams must perfect the process of providing them with relevant information.
An average enterprise has a three to five person CI team serving 500 stakeholders, a 2021 Evalueserve study reports.
CI teams must leverage AI to proactively source and filter diverse nuggets of information. How do professionals tailor these massive amounts of data for each team’s needs? They integrate the power of AI in competitive intelligence programs to get action-ready decisions.
So, what is Human-AI Collaboration?
Collaborative intelligence characterizes multi-agent, distributed systems where each agent, human, or machine contributes to a problem-solving network.
These systems accomplish complex goals by combining the power of AI and people to propagate superior results and get better through continuous learning from one another.
Benefits of Human-AI Collaboration
Combining AI and human intelligence results in less repetitive and reactive work in intelligence teams and provides huge opportunities to scale programs. But does that mean AI will replace the CI? – Not at all, but CI increases the team’s value by enabling professionals to focus on strategic and impactful work, on interpreting data to drive business impact.
While AI creates efficiency and gathers, filters, and summarizes intelligence; the CI team can focus on providing analysis that helps the company make decisions.
Some human-AI collaboration benefits include increased end-to-end efficiency, improved ability to extract insights, well-tailored customization for your needs, and better ROI.
Results
When struggling to deliver meaningful insights to over 2,000+ internal stakeholders, Syngenta’s CI team configured AI to collect, filter, and visualize key intel and used domain experts to contextualize insights for stakeholders so they were immediately actionable. This resulted in a 174% increase in content user subscriptions, a 34% increase in active users, and improved team collaboration.
Due to the COVID-19 pandemic, a big four advisory firm faced challenges with the number of disrupted business models they could help advise. The firm asked Evalueserve to help them efficiently sift through data to find relevant sales opportunities.
Our CI program enabled the client to monitor buying triggers like bankruptcy and set up filters to exclude businesses already engaged with a competitor. The resulting optimization allowed them to focus on strong-fit opportunities. The firm reduced time to market by 35%, and they saw a 300% improvement in lead identification and a 60% increase in lead conversion.
For more information on how CI programs, AI with human collaborations work, download our white paper, The Ultimate Guide to Integrating AI into Competitive Intelligence Programs.
84% of C-suite executives believe they must leverage AI to achieve their growth objectives. Given the overwhelming amount of data available, it makes sense to discover ways for technology to reduce the burdens of menial, repetitive tasks for CI professionals, reducing errors and turning insights into action along the way.
Find out how you can blend the power of AI and Competitive Intelligence to your benefit. Speak to one of our experts today: https://www.evalueserve.com/speak-to-expert/
