Published on April 25th, 2024
The advent of OpenAI’s ChatGPT marked a pivotal moment in the software industry, igniting a race towards generative AI with its debut in November 2022.
Software as a Service (SaaS) providers are now in a frenzy to enhance their tools with advanced productivity features driven by generative AI.
GenAI tools serve a myriad of purposes, simplifying software development for coders, aiding sales teams in crafting routine emails, empowering marketers to generate unique content affordably, and fostering creativity by facilitating idea generation among teams and creatives.
Notable recent launches in the GenAI realm include Microsoft 365 Copilot, GitHub Copilot, and Salesforce Einstein GPT.
These offerings, provided by leading SaaS vendors, come with a price tag, signaling the lucrative potential of the GenAI revolution that no provider wants to overlook.
Google is also poised to unveil its SGE (Search Generative Experience) platform, offering premium AI-generated summaries in lieu of conventional website listings.
Given this rapid progression, it’s only a matter of time before AI capabilities become standard features in SaaS applications.
However, the advancement of AI in the cloud landscape also introduces new risks and challenges for users.
The widespread adoption of GenAI applications in work environments is swiftly giving rise to concerns about heightened exposure to a new wave of cybersecurity threats.
You May Also Like: How SaaS Startups Are Changing The World For The Better
GenAI: Boon or Bane? How To Mitigate The Risks
GenAI operates by training models to create new data that closely resembles the original data provided by users.
Currently, ChatGPT is cautioning users upon login, advising them not to share sensitive information and to verify facts.
When questioned about the risks associated with GenAI, ChatGPT acknowledges that data submitted to AI models like itself may be utilized for model refinement, potentially exposing it to researchers or developers working on these models.
This exposure broadens the vulnerability of organizations that share internal data in cloud-based GenAI systems.
Emerging risks include the potential for intellectual property leakage, exposure of sensitive customer data and Personally Identifiable Information (PII), and the misuse of deepfakes by cybercriminals for phishing and identity theft.
These concerns, coupled with the challenges of meeting compliance and governmental regulations, are leading to pushback against GenAI applications, particularly within industries and sectors handling confidential information.
A recent Cisco study revealed that over a quarter of organizations have already prohibited the use of GenAI due to privacy and data security concerns.
The banking industry was among the earliest to impose a ban on GenAI tools in their workplaces.
While financial services leaders recognize the potential benefits of leveraging artificial intelligence for efficiency and support, 30% still enforce a ban on generative AI tools within their organizations, as indicated by a survey conducted by Arizent.
In a recent development, the US Congress enacted a ban on the use of Microsoft’s Copilot on all government-issued PCs to bolster cybersecurity measures.
Catherine Szpindor, the House’s Chief Administrative Officer, stated that Microsoft Copilot was deemed a risk by the Office of Cybersecurity due to the potential leakage of House data to unauthorized cloud services.
This ban follows the government’s previous decision to block ChatGPT.
Who’s In Charge? The Urgent Need For GenAI Oversight
Aside from reactive bans on GenAI, organizations are facing significant challenges in effectively regulating its usage as these applications infiltrate workplaces without proper training, oversight, or employer knowledge.
A recent study by Salesforce reveals that over half of GenAI adopters utilize unapproved tools within their work environments.
Despite the potential benefits offered by GenAI, the absence of clearly defined policies regarding its usage poses risks to businesses.
However, there’s hope for change on the horizon, especially with new guidance from the US government aimed at strengthening AI governance.
In a recent statement, Vice President Kamala Harris instructed all federal agencies to appoint a Chief AI Officer with the necessary experience, expertise, and authority to oversee all AI technologies and ensure their responsible usage.
With the US government taking proactive steps to promote responsible AI utilization and allocate resources for risk management, the focus now shifts to developing safe methods for app management.
You May Also Like: Six Reasons Why SaaS Can Be Right For You
Taming The Titans: Taking Back Control Of GenAI Apps
The GenAI revolution introduces risks that often lurk in the realm of the unknown, presenting a challenge as traditional perimeter protection measures become outdated.
Today’s threat actors increasingly target vulnerabilities within organizations, such as human and non-human identities, as well as misconfigurations in SaaS applications.
Recent tactics employed by nation-state threat actors include brute-force password attacks and phishing schemes, resulting in successful delivery of malware, ransomware, and other malicious activities within SaaS environments.
The hybrid work model blurs the lines between personal and professional device usage, further complicating SaaS application security efforts.
Given the allure of GenAI’s capabilities, it’s inevitable that employees will gravitate towards its use, whether officially sanctioned or not.
The rapid integration of GenAI into the workforce should prompt organizations to reassess their security infrastructure to combat the next wave of SaaS security threats.
To regain control and visibility over SaaS applications with GenAI features, organizations can leverage advanced zero-trust solutions like SSPM (SaaS Security Posture Management).
These solutions enable the utilization of AI while rigorously monitoring associated risks.
Gaining insights into every AI-enabled application and assessing its security posture empowers organizations to proactively prevent, detect, and respond to emerging threats in the SaaS landscape.
Some Key Points
- Prioritize Security: Implement zero-trust security solutions like SSPM to gain control and visibility over GenAI-powered SaaS applications. Proactive threat detection and response are crucial.
- Develop Clear Policies: Establish clear policies around GenAI usage within your organization. User education and training are essential to mitigate risks associated with unauthorized tools and data exposure.
- Embrace Responsible AI: Support initiatives promoting responsible AI development and usage. Advocate for clear government regulations that address privacy, data security, and intellectual property concerns.
Conclusion
The GenAI revolution presents a double-edged sword for SaaS applications. While it unlocks a new era of productivity and creativity, it also introduces significant security risks.
Organizations must navigate this landscape cautiously, balancing innovation with robust security measures.
The future of work will be increasingly shaped by AI. By adopting a security-first approach and embracing responsible AI practices, organizations can harness the power of GenAI while safeguarding their data and fostering a secure digital environment.
