How MSPs can help you harness the power of generative AI

Generative AI and large language models (LLMs) like ChatGPT are a scorching hot topic right now, and for good reason. A recent MIT study shows that LLMs can improve worker productivity by 50 percent in white-collar settings. Consequently, more than half of C-suite members globally (56 percent) feel pressured to adopt comprehensive GenAI tools during the next year -- yet two in three fear the consequences of rapid GenAI adoption, particularly as it applies to disinformation and data governance.

Leaders are overwhelmed by the prospective benefits -- and consequences -- of adopting GenAI. They may be surprised to learn that a managed service provider (MSP) can assuage their worries and prepare their organization for this newest iteration of digital transformation.

Addressing AI challenges with an MSP

When an organization outsources key processes to MSPs, its internal stakeholders are better prepared to interact with AI systems. That’s because MSPs can prepare chief information security officers (CISOs) and IT leaders for the immense digital transformation that GenAI processes require.

To that end, MSPs help to facilitate the following crucial tasks:

• Data cleansing and quality assurance -- MSPs help organizations clean and validate their sprawling data reserves, ensuring all data remains unique, high-quality and error-free. This process significantly improves the accuracy and performance of LLMs and other GenAI tools.
  
  Data quality is of the utmost importance when interacting with AI. Even simple mistakes in a data set can create highly problematic inaccuracies. To understand why, consider the tenants of conditional arguments. "If this, then that" statements are only logical when based on correct suppositions. Basing an automated task on a flawed conditional argument -- or asking ChatGPT to answer a question based on incorrect data -- may disrupt your system’s operations by generating an incorrect output or command.
  
  To clean and validate data, MSPs can use various tools and techniques, from profiling and scrubbing to deduplication. MSPs can also help organizations develop best practices for data governance, enabling responsible data usage and storage as businesses scale.

• Employee training initiatives -- GenAI is a promising tool for nearly every department, so it may be difficult to pinpoint individual use cases at the outset of adoption. MSPs fill this knowledge gap by providing generalized data and AI effectiveness training, including online courses, instructor-led webinars and on-the-job training. Moreover, leading MSPs can streamline an organization’s IT footprint, making user access far less complex and, ultimately, more secure.
  
  Boosting employee awareness of GenAI’s benefits -- and shortcomings -- is essential. For example, employees should understand the consequences of inputting sensitive or confidential information into a self-learning LLM. Additionally, using GenAI can increase an organization’s attack surface. With the proper training, employees can self-manage and mitigate these risks.

• Bolster cybersecurity protocols and fail-safes -- MSPs can help organizations implement additional security measures to protect GenAI models from unauthorized access or misuse, preventing security breaches and data loss. Employee training is an important piece of this puzzle but not enough in isolation. MSPs bridge the gap by facilitating the adoption of other vital security measures like access control, encryption and anomaly detection.
  
  GenAI systems are particularly vulnerable to sponge and inference attacks as well as data management risks like data leakage and intentional data poisoning. Perhaps just as important, the existence of LLMs is increasing the maturity of common schemes like phishing, which account for a significant proportion of data breaches. Industry research indicates that phishing attacks increased by 45 percent in 2022.
  
  MSPs can combat these troubling trends by bolstering an organization’s overall security posture through offerings like continuous penetration testing, managed detection and response (MDR) and ransomware protection as a service (RPaaS).

Getting started with an MSP today

MSPs guide leaders through the responsibilities mentioned above. However, the nuances of each strategy will differ based on an organization’s needs. To ascertain those needs, MSPs should:

• Conduct a readiness assessment, including audits of an organization’s transparency, ethics, data sources, data stewardship and regulatory requirements.
• Identify a problem statement and quantify apparent data issues.
• Assign an executive-level owner or sponsor of the GenAI adoption plan.

Together, these tasks help to identify an organization’s leading issue with data, which informs the strategy an MSP takes on day one of the partnership. For example, many organizations may benefit from early on-the-job training before data cleansing efforts; for others, data cleansing is the top priority and should be conducted ASAP.

Regardless, leaders should ensure their MSP crafts a unique strategy that conforms to their organization’s specific needs.

Looking to the future of GenAI

GenAI’s future is ripe with potential. These systems can increase data’s value by intelligently augmenting and automating the customer, consumer, patient and citizen experience. GenAI is also increasing organizational trust in large data sets by slowly but surely eroding bias.

Yet, GenAI’s potential invokes responsibility. Leaders must examine its ethical and regulatory implications before diving headfirst into the realm of LLMs. MSPs will play an incredibly vital role here, ensuring the effective deployment of GenAI and increasing organizations’ overall IT infrastructure and security posture for the years to come.

Image credit: ArtemSam/depositphotos.com

Jonathan Lerner is CEO and president of InterVision, a leading managed services provider, delivering and supporting complex IT solutions for mid-to-enterprise and public sector organizations throughout the US. Jonathan has spent the last two decades inspiring high-performance teams to define market differentiating strategies that deliver operational excellence and drive profitable revenue growth. His executive leadership spans multiple industries including financial services, capital markets, technology services, professional and managed services, retail, logistics, distribution, public sector, and telecom.