We hear of the many benefits of implementing AI into workflows, but what is the best way to do this, particularly for SMEs? It can be overwhelming to hear about all the different AI programs which are available, and SMEs always need to keep their budget in mind. Sandy Kahrod, Product Manager: Modern Work at Six Degrees, discusses what key challenges organisations face when integrating AI technologies into their existing workflows and what to consider during the implementation.
Today’s AI-powered tools offer numerous benefits – from chatbots and virtual assistants that improve customer engagement and deliver a better employee experience, through to intelligent automation that streamlines operational processes, improves productivity and generates efficiency savings.
SMEs know that AI has the potential to put them on a level playing field with larger corporations, whether that’s enabling new capabilities or delivering data-driven insights that support better decision-making and make it easier to spot business opportunities. However, research undertaken by the British Chambers of Commerce reveals many SMEs are stuck in neutral when it comes to moving ahead with their AI adoption plans.
While AI is an alluring proposition, knowing where and how to start can be intimidating. The following guidelines will help ensure that SMEs can progress their real-world AI aspirations in a pragmatic and cost-contained way.
Understand the key challenges
While AI is readily available via solutions like Copilot and ChatGPT, integrating AI into work practices is not always as straightforward as it first seems. This is something that can prove a stumbling block for large enterprises, as well as smaller business entities.
While AI projects don’t necessarily require million-dollar budgets to be successful, organisations need to be mindful of the potential upfront costs and disruption that can be associated with AI implementations. Without the right planning, the path to implementation can be a rocky one. Not every SME has the budget for a custom-build AI solution, so identifying cost-effective pre-built AI tools that offer clear ROI potential is a key consideration.
However, AI isn’t always a ‘plug and play’ solution. In addition to the software itself, organisations may need high-performance hardware and data storage upgrades capable of handling the compute resources involved. That said, ‘pay as you go’ cloud-powered AI models that offer flexible pricing options and can be tailored to specific business requirements are now much more readily available.
Other key areas to focus on include putting the right cybersecurity and compliance measures in place, cleaning and preparing data so it can be leveraged by AI tools, and training and upskilling personnel across the business. Although AI can often be seen as something that creates security issues, a lot of the time it in fact brings pre-existing gaps in cybersecurity to light, furthering the need for thorough security protocols prior to its implementation.
Getting started: Preparation is all
Identifying areas where AI is most likely to deliver the most significant impact is a critical first step. AI’s primary strength lies in its ability to assist with specific tasks such as automating repetitive manual processes and analysing large datasets. So solutions that address core challenges or will generate new value-add in areas such as marketing, sales or logistics and back office administration tasks will also present prime opportunities.
Setting clear strategic objectives that are focused on core business needs will be important for maximising outcomes such as using chatbots to handle customer queries, optimising inventory, enabling product personalisation or gaining deeper customer insights.
Ideally, AI projects should be focused on activities where success can be monitored and measured. For example, an online retailer that wants to alter deals dynamically to minimise losing sales could use AI to predict stock requirements and optimise offers in real-time depending on product availability. Undertaking a like-for-like comparison with previous campaigns will reveal how AI contributed to improvements in sales volumes and margins.
Security and data privacy
Data protection and regulatory compliance is a must have and SMEs will need to choose solutions that feature robust data protection mechanisms. To assure compliance with privacy and security regulations such as GDPR and NIST 2, SMEs will need to implement comprehensive governance frameworks and controls to ensure that customer, employee, financial or IP data is not inadvertently exposed.
AI ethics and bias poses another challenge. AI systems learn from large databases and, without the right oversight, can perpetuate existing biases that lead to unfair or discriminatory outcomes. To prevent this, SMEs will need to implement checks and balances to mitigate this risk.
Finally, SMEs need to ensure that AI responses do not deviate from socially acceptable norms. Stories about rogue chatbots abound, so SMEs will need to ensure that testing and feedback loops are in place so they can refine and fine-tune the models they use.
Integration and data management
Legacy infrastructures may not be compatible with modern AI solutions and SMEs may need to overhaul their underlying IT infrastructure to accommodate new AI integrations. In addition to addressing compatibility issues, additional security measures – such as access controls and encryption – will be required to maintain the integrity of AI systems.
Data is the lifeblood of AI, but before AI can be put to work it needs high-quality and clean data. So SMEs will need to ensure their data is accurate, detailed and appropriately prepared in readiness for their AI implementations. Strong data management capabilities, including policies and practices that cover data collection, storage and usage will be important to mitigate compliance risks.
AI expertise and workforce adaptation
Partnering with specialists that can provide technical support and expertise will significantly accelerate and ensure the successful deployment of AI solutions. This is particularly the case for SMEs that need to be certain they can navigate any complexities that may come up and are deploying the right solutions for their needs.
Subject matter experts experienced at rolling out AI tools such as Copilot company-wide can ensure that departmental and function-by-function data and processes are appropriately incorporated and that AI models are built accurately and deliver appropriate outcomes.
Prior to implementation, SMEs should prepare and reassure employees. Providing regular communications and training will address concerns that ‘AI is taking our jobs’ and ensure that the workforce is positive about the benefits of engaging with AI platforms.
Stepping into an AI future
With the right planning and preparation, SMEs can apply AI to multiple processes and operational challenges. Rather than taking a ‘big bang’ approach, SMEs should aim to take small incremental steps and implement AI in phases. This approach will make it easier to manage costs, mitigate risks and gain valuable experience along the way.
Today’s cloud-based tools and user-friendly open source options now make AI more attainable and cost-effective for SMEs than ever before. Even with limited AI budgets, SMEs can unlock the potential of AI and enable tailored solutions that address their specific business needs.