Explore how AI is transforming businesses across various sectors, from marketing to IT, driving innovation and efficiency. Understand the importance of data, identity management, and responsible AI adoption for future growth and security.
Today, almost every organisation and most individuals are using or experimenting with Artificial Intelligence (AI). There are plenty of examples of how it is improving businesses, from marketing and HR to IT teams. What was once computationally impossible or prohibitively expensive is now within reach with the use of AI.
According to Gartner, approximately 80% of enterprises will have used generative AI (GenAI) APIs or models by 2026. As AI drives value for organisations, it is fuelling further demand and adoption.
In our modern digital environment, we have a phenomenal amount of data we can now use to train OpenAI’s ChatGPT and other GenAI models. AI can more naturally engage data that lives in the online world, capturing certain activities and events to provide more information and context. In particular, AI’s capability for analysing disparate data sets, identifying patterns, and predicting trends is extremely valuable for IT leaders.
87% of survey respondents are planning to use AI
Unsurprisingly, in our latest SME IT Trends Report, surveyed organisations were actively planning for AI. In fact, only 13% of global organisations said they had no plans to implement AI initiatives. Well over half of surveyed respondents (61%) expect to implement AI initiatives within the next year. 76% agreed their organisation should invest in AI, and 63% have already developed an AI policy.
However, one of the challenges around AI is how these large language models (LLMs) dig into complex subjects. There is a lot of superficial or incorrect data, which creates limitations for LLMs. For example, they can only look at data that is available. In other words, LLMs predict the best next word based on what has already been provided. This is great if you want help with anything text-related, however, accuracy and context are critical, because results generated by AI solutions will drive business and security decisions.
Indeed, while AI presents breakthroughs in the ability to process logic differently, it also blurs the lines between humans and machines. This is why identity management is crucial to ensure that organisations can securely connect people to technology.
Why AI is an IAM game-changer
Integrating AI in identity and access management (IAM) is a game-changer for businesses looking to provide their users a secure and seamless experience. Its capabilities can introduce more accurate, efficient, and adaptable identity management solutions that could make friction-filled, cumbersome identity management a thing of the past. In reality, AI technology has already begun to revolutionise how businesses manage identity and access, making it more secure and efficient.
AI in identity management has the potential to resolve a host of issues related to the dynamic nature of identity and user behaviours. For example, the need for more robust security measures, the complexity of managing large datasets, and the requirement for adaptive authentication methods in today’s diverse and dynamic work environments.
Therefore, rather than futile attempts to slow innovation and restrict AI use, we must harness AI’s power responsibly without introducing unnecessary risk. With AI still in its infancy, it is time to ensure the guardrails are in place. Where there is an opportunity, there is also a threat.
AI could be a weakness in a company’s security
AI solutions are also attracting close attention from threat actors who are realising that while they can be used by companies to identify security weaknesses and address them, they could themselves be weaknesses in a company’s security posture.
To this point, according to a recent Gartner Peers Insights Poll around how software teams are using GenAI, 38% of respondents cited issues around cybersecurity, and a similar percentage also cited governance policy problems, while 41% said the cost of AI tools was a challenge.
As a plethora of new AI capabilities come to market, there is a need for better oversight and governance of AI. Particularly, as AI systems process vast amounts of sensitive data, organisations must prioritise data privacy and adhere to regulatory requirements. This includes implementing data anonymisation techniques, ensuring secure data access protocols, and considering local data processing to minimise the risk of data breaches and ensure compliance with data protection laws.
Put simply, organisations looking to bolster security protocols and improve user experience can’t ignore the complexities of data privacy and ethical considerations. Nor can they ignore the fact that AI can be wrong. While an error rate of 15% may not look bad on paper, when dealing with sensitive data like PII, this could lead to significant financial and reputational damage.
Speed is often prioritised over risk management
AI is intuitive, versatile, and useful. Integrating AI into identity management can create better IAM solutions and make IT admin teams faster and more productive. However, businesses must caution against trying to make things happen too quickly, which could have a detrimental effect. Therefore, organisations looking to enhance security measures through AI must approach new initiatives through a strategic and thoughtful application approach.
The GenAI revolution is different from anything that has come before it. AI is set to change how we work, reinvent processes, create new opportunities, and change how IT teams work. However, many organizations lack formal governance policies around AI, which could open them to future risks. The intersection between AI and identity is pivotal to securely connecting people to technology while enhancing identity management through AI.
Joel Rennich, VP of Product Strategy at JumpCloud.
Joel Rennich is the VP of Product Strategy at JumpCloud. He focuses primarily on the intersection of identity, users, and their devices. At JumpCloud, he leads a team focused on device identity across all vendors. Before JumpCloud, Joel was a director at Jamf, helping to make Jamf Connect and other authentication products.
