Key Takeaways
Did you know that 84% of business leaders believe AI and emerging technologies give them a competitive advantage? However, they often overlook the associated risks. Let’s examine how to maintain a proper balance.
Emerging technologies and artificial intelligence are revolutionizing industries by automating labor-intensive tasks and generating insights from data. This potential encourages organizations to quickly adopt these technologies.
The rush to adopt these powerful technologies can cause companies to ignore the inherent risks. Organizations need to establish a solid base, assess potential dangers, build upon existing processes, and plan for unexpected challenges as they adopt new technologies.
When an organization decides to integrate a new technology solution, determining the initial steps can be challenging. Hastily adopting technology might lead to overlooking minor issues that could escalate into significant problems, such as scalability concerns, access control, and unforeseen outcomes. Conversely, excessive delays can hinder the benefits of these tools by negating efficiencies and introducing opportunity costs.
Leadership does not need to have immediate solutions for every issue. Instead, critical factors need thorough evaluation, including cybersecurity and regulatory compliance. As security and compliance demands evolve alongside technological advancements, organizations might not be fully aware of specific requirements. Nevertheless, several best practices can be adopted to prepare effectively for the emergence of AI standards:
As organizations adapt to evolving regulations and heightened security needs, they must also address the current risks inherent in their operational landscapes. Data acts as the critical foundation for AI and emerging technologies, yet it is also a prime target for cybercriminals and other malicious entities. A key challenge for businesses is ensuring data accessibility for legitimate stakeholders and systems while implementing robust security controls.
Initiating effective risk management involves adopting established control frameworks such as NIST CSF, ISO 27001, or NIST 800-53. These cybersecurity frameworks aid in assessing how and where data is stored, enhancing the security measures across the organization. Implementing a secure, cloud-based environment helps safeguard data, allows essential access for necessary personnel and systems, and prevents data from being isolated in vulnerable locations like local desktops or external drives.
To safeguard sensitive data, businesses must implement stringent controls that restrict access to authorized people and software. Many organizations are familiar with the principles “least privilege” and “zero trust,” which dictate that access to information resources is granted solely based on necessity. The introduction of AI technologies complicates these dynamics, necessitating more nuanced control mechanisms.
AI operates as effectively as the data it processes, emphasizing the need for high-quality, relevant data for its functions. Should AI systems access or analyze irrelevant or inaccurate data, the resulting outputs could be flawed. Such errors have the potential to infiltrate decision-making and compliance reports, leading to adverse consequences.
Furthermore, the integration of third-party applications introduces additional complexities. Collaborating with external entities often requires sharing access to specific data and systems essential for their operations. Like internal processes, it is critical for businesses to ensure that these third parties are granted access only to the data they genuinely need, maintaining stringent oversight to protect organizational integrity and compliance.
Proper preparation and security considerations are foundational, yet the adoption of new technology can still present challenges. While some AI and software solutions may seamlessly integrate with existing workflows, it is crucial for organizations to conduct thorough training for stakeholders and users throughout the implementation process. Adapting existing policies and training protocols can streamline the integration of new technologies.
Organizations with established information security and data classification and handling policies often possess robust data management and control frameworks suitable for AI applications. If these frameworks are already in place, they can be extended to include new technological deployments. Conversely, if a secure data handling framework is not yet established, businesses may need to develop and implement new programs and policies for their teams to ensure proper handling and security.
Systems integration is critical when introducing new software, particularly as it relates to a comprehensive data strategy. Effective data governance is essential for managing data-driven technology, but compatibility with existing systems cannot be assumed. IT teams must conduct tests and operations to confirm that legacy systems function well with new software additions. This proactive approach not only reinforces your data strategy but also helps identify potential inefficiencies and security concerns, ensuring a smoother transition and integration of new technologies within the existing infrastructure.
Emerging technologies bring not only unexplored potential but also unfamiliar threats. In today’s environment, it is not a question of whether a cybersecurity incident will occur, but when. Despite the rise of novel and unprecedented cyber threats, organizations can effectively prepare for potential breaches.
Developing a comprehensive, proactive incident response plan is crucial for managing the disruption following a cybersecurity incident. This plan should clearly define the roles and responsibilities of individuals and teams, outlining the necessary steps they must take in the event of a breach. Additionally, the plan should include protocols for clear and effective communication about the incident, both internally to the organization and externally to clients and the public. This strategic preparation helps mitigate the operational and reputational impacts of cyber threats and strengthens the organization’s resilience against future disruptions.
Emerging technology and AI are sources of optimism for organizations, offering numerous benefits that can transform operations. However, in the rush to adopt these technologies it is crucial for companies to temper their enthusiasm with a measured approach. An all-or-nothing strategy is not advisable. Instead, AI and emerging technologies should be deployed incrementally, starting with small-scale projects to gauge effectiveness and integration challenges before a full-scale roll-out across the organization.
By leveraging existing operating procedures and assessing how new technologies can enhance these practices, organizations can realize the advantages of innovative solutions while safeguarding against potential setbacks. This careful, thoughtful approach helps ensure that technological advancements contribute positively to the organization without disrupting established systems and processes and introducing unnecessary risk.
As your organization explores the exciting potential of AI and emerging technologies, partnering with LBMC can ensure you navigate this new territory with confidence. Our expert teams are proficient in cybersecurity frameworks like NIST, ISO 27001, and SOC, and are ready to tailor security solutions that protect and enhance your technological investments.
With LBMC, your venture into innovative technologies is grounded in proven expertise and comprehensive risk management strategies, ensuring that your business not only survives but thrives in the digital age. Let LBMC guide you through every step of your technological evolution, securing your operations and fostering sustainable growth.
Content provided by LBMC Senior Manager, Brian Willis. He can be reached at brian.willis@lbmc.com or by phone at 615-309-2607.
Brian Willis is an information security consultant, auditor, and analyst with over 25 years’ experience in diverse technology roles. From his beginnings as a systems analyst in small manufacturing environments Brian has at one time or another, and often at the same time, served as network engineer, client/server administrator, help desk technician, pen tester, and compliance manager. Leveraging his managerial and administrative experience with his knowledge of regulatory compliance and security principals, Brian delivers practical guidance to his clients to ensure they achieve their goals and add value to their organizations. Brian has been a PCI Qualified Security Assessor for over 15 years, leading assessments in the food service, retail, healthcare, insurance, and payment system sectors.
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