How AI Can Elevate Your Business Processes And Increase Productivity by 40%

If there's one lesson we've gained from the past several years, it's this — artificial intelligence (AI) is here to stay, and it's only getting better over time. 

How do we know this? The AI market is set to reach a valuation of half a trillion dollars in 2023 alone…which means that we can expect more competitive features, ongoing growth, and routine integration of machine learning concepts in every aspect of our daily lives. (Cool, right?)

But what does this look like in our day-to-day business functions? It's a valid question, as the concept of AI in business has evolved over time, moving from use in fractional applications and sci-fi flicks to daily, transformative use across the business landscape.

Understanding how to leverage AI in your daily business flow is the first step toward sustainable and efficient business processes for years to come. Read on to learn how experts like you can use AI to increase your business' productivity by 40% (minimum!). 

Understanding AI and Productivity

Artificial Intelligence (AI) pertains to the development of computer systems capable of executing tasks that traditionally demand human intelligence. These tasks encompass learning, reasoning, problem-solving, perception, language comprehension, and decision-making.

The fundamental objective of AI is to engineer machines that can replicate, simulate, or even surpass human intelligence, thereby addressing intricate challenges and enhancing overall efficiency.

AI encompasses various categories, among which Narrow AI (or weak AI) stands out. Narrow AI is purpose-built for specific tasks, exhibiting limited capabilities tailored to predefined functions.

Conversely, General AI (or strong AI) remains a theoretical concept. It envisions the creation of machines endowed with human-like thinking and learning capabilities, possessing consciousness and self-awareness.

Machine learning, a pivotal component of AI, involves training computers to acquire knowledge and refine their performance through experience, eliminating the need for explicit programming.

Deep learning, a subset of machine learning, focuses on instructing artificial neural networks using extensive datasets to discern patterns and make informed decisions based on them.

In a landscape dominated by subtractive productivity, AI emerges as a transformative force driving change and innovation. Its impact spans diverse domains such as automation, robotics, natural language processing (NLP), computer vision, and autonomous driving. This technology heralds a paradigm shift in how we approach problem-solving and efficiency in the contemporary world.

Productivity serves as the metric for measuring the output produced per unit of input, often expressed as a ratio. In the realms of business and economics, productivity stands as a pivotal indicator, reflecting a company's or a country's proficiency in converting resources into goods and services with efficiency.

The assessment of productivity is instrumental in evaluating resource utilization effectiveness, fostering growth, and ultimately elevating the standard of living.

Numerous critical factors exert influence on productivity:

• Technology: Modern technological advancements, encompassing automation and software utilization, exert a direct impact on productivity. These technologies streamline processes, mitigate errors, and save time. Among these, Artificial Intelligence (AI) plays a pivotal role in boosting productivity by integrating advanced algorithms and machine learning into various operational aspects.
• Human Capital: The knowledge, skills, and abilities of the workforce are pivotal contributors to productivity. Well-trained and skilled employees operate with enhanced efficiency, making substantial contributions to overall productivity levels.
• Management Practices: Efficient management practices, encompassing strategic planning, organizational effectiveness, and clear communication, significantly influence productivity. Strong leadership and effective decision-making lead to improved resource allocation and heightened productivity levels.
• Innovation: Innovation serves as a driving force, allowing businesses to create novel products, services, and processes. These innovations contribute to increased efficiency and overall productivity by introducing streamlined approaches to various operations.
• Infrastructure: Access to reliable and effective infrastructure, spanning transportation and communication networks, acts as a catalyst for enhanced productivity. A well-established infrastructure reduces logistical constraints and facilitates the seamless flow of goods and information.

Integrating AI into businesses to enhance productivity is a nuanced undertaking. It necessitates a profound understanding of business processes, adjustments in workflows, and comprehensive training for the workforce to adapt to new technologies and transition between different productivity styles.

Nevertheless, the potential benefits of AI, including cost reduction, resource optimization, and overall productivity growth in manufacturing, justify the investment in this transformative technology. The incorporation of AI aligns with the broader goal of fostering efficiency and innovation in the business landscape.

1.AI Improves Email Deliverability

There are approximately 4 billion daily email users on the World Wide Web—which means you can reach 4 billion people every day. (Or at least whoever's on your email list).

Email deliverability is a key area of focus for businesses across B2B and B2C arenas. It ensures you deliver the right message to the right audience in the right way. AI can help with that, helping you to hit your benchmarks in the most cost-effective way yet.

When your deliverability is suspect, it causes all types of problems across the breadth of your marketing campaigns. There are risks your emails could get flagged as spam, hurting your reputation and ability to effectively deliver campaigns in the future. Beyond that, you're burning man-hours when you send campaigns that do deliver as they should, hurting the overall return on investment you're placing into your marketing budget.

Regarding email marketing, AI tends to take two approaches: Proactive support and acute support.

Here's how you can benefit from each: 

Proactive Support: AI Removes Barriers To Success 

 Effective email campaigns often encounter challenges such as invalid email addresses, inconsistent campaign sends, and the unwarranted labeling of legitimate content as spam. The encouraging news is that these impediments can be mitigated and even avoided altogether by leveraging sophisticated AI solutions. These technological fixes are designed to address these concerns proactively, working collaboratively with your team to enhance the efficiency of your email marketing strategy.

Acute Support: Gather Data-Driven Insights Using AI Tools 

2.AI Simplifies Finance Processes and Boosts Profits

The accounts payable automation market could reach $8.3 billion by 2031 according to Allied Market Research—which makes sense when you consider an AI-driven system saves $3-$9 per invoice on average.

These savings come in the wide-ranging form of system-wide efficiency improvements. 

Here are some examples:

• Manual error reduction: Humans make mistakes. While AI can, too, these instances are far less frequent than you can expect to see with manual reconciliation processes. Many companies use AI in their accounts payable flow to reduce liability overall—and minimize extra time and money spent on bookkeeping fixes. We know this seems merely inconvenient on the surface. However, an error rate of 2% (the average rate you'll see with manual reconciliation steps according to the American Productivity & Quality Center) can be reduced to 0.08% using AI — which could save 10% or more of a team member's time in a company that processes 200 hours worth of accounting work. That's a lot!
• Faster processing: Money in, money out. Mastering your processing schedule and optimizing steps to get an invoice out the door puts money back into your pocket—giving you a near-instant profit boost for the month or quarter.
• Better ROI: These changes add up quickly, resulting in increased return on investment (ROI) for your team members and stakeholders. A well-run finance department creates positive momentum that fuels an organization, teeing you up for some seriously powerful ripple effects. 

Considerations and Challenges in Implementing AI Solutions

• ​Data Quality and Accessibility:  The foundation for successful AI implementation rests on the availability of high-quality data, which serves as the lifeblood for AI algorithms to learn and make informed decisions. Ensuring data accuracy, representativeness, and freedom from biases is pivotal, as poor data quality can lead to skewed results, rendering AI solutions ineffective or even counterproductive. Furthermore, the challenge extends to the accessibility of relevant data, with organizations frequently contending with data silos that hinder the seamless flow of information necessary for AI applications. Bridging these gaps necessitates a concerted effort to establish robust data governance frameworks, dismantle silos, and implement processes for ensuring data quality.
• Ethical and Regulatory Considerations: As AI implementation proliferates, ethical considerations loom large in the minds of businesses and society. Issues such as algorithmic bias, privacy infringements, and potential misuse of AI technologies raise important ethical questions. Organizations must prioritize transparency and fairness in their AI systems to build trust among users and stakeholders. In addition to ethical concerns, the regulatory landscape surrounding AI is in a constant state of flux. Compliance with data protection laws, industry-specific regulations, and emerging AI guidelines is essential to avoid legal repercussions and maintain ethical standards. Navigating this intricate terrain requires a proactive approach, with organizations investing in robust ethical frameworks and staying abreast of evolving regulatory requirements.
• Talent Acquisition and Skill Gaps: The effective implementation of AI solutions demands a workforce equipped with the right skills and expertise. However, the demand for AI talent far outstrips the current supply, leading to a significant skills gap. Attracting, training, and retaining professionals with expertise in machine learning, data science, and AI development poses a considerable challenge. To address this, organizations should invest in ongoing training programs, collaborate with educational institutions, and foster a culture of continuous learning. Additionally, exploring partnerships with external experts or leveraging AI-as-a-service solutions can help augment internal capabilities.
• Integration with Existing Systems: Integrating AI solutions with existing systems presents a substantial challenge for organizations. Legacy systems, outdated infrastructure, and incompatible technologies can impede the seamless adoption of AI. The integration process often requires substantial time, resources, and careful planning to avoid disruptions to day-to-day operations. A phased approach to integration, gradually introducing and testing AI solutions, can help mitigate risks and streamline the transition. Furthermore, investing in interoperability and ensuring effective communication between AI systems and other technologies is crucial for a harmonious integration process.
• Cost and Return on Investment: While the potential benefits of AI are vast, the initial costs of implementation can act as a significant barrier for many organizations. The expenses associated with acquiring technology, hiring skilled professionals, and ongoing maintenance can strain budgets. Calculating the return on investment (ROI) for AI initiatives is complex, as the benefits may take time to materialize or be challenging to quantify. Conducting thorough cost-benefit analyses, considering both short-term and long-term impacts, is essential. Identifying quick-win opportunities and prioritizing high-impact use cases can help organizations realize tangible benefits early in the implementation process, justifying the initial investment and building momentum for further AI adoption.
• Security Concerns: AI systems, highly reliant on data, are susceptible to security threats. The increased connectivity and interdependence of AI applications within an organization's ecosystem make them potential targets for cyber attacks. Ensuring the security and integrity of data used by AI algorithms is paramount to prevent unauthorized access, manipulation, or exploitation. Implementing robust cybersecurity measures, encryption protocols, and conducting regular security audits are essential components of safeguarding AI solutions. Organizations should remain vigilant to emerging threats and update their security measures accordingly to stay one step ahead of potential attackers.
• User Acceptance and Change Management: The introduction of AI solutions often necessitates a cultural shift within an organization. Resistance to change, fear of job displacement, and a lack of understanding about AI can hinder user acceptance. Effective change management strategies are essential to address these concerns and foster a positive attitude towards AI adoption. Clear communication about the benefits of AI, involving employees in the implementation process, and providing adequate training and support are crucial steps in overcoming resistance. Organizations must emphasize the augmentation rather than replacement role of AI, highlighting how it can enhance human capabilities and contribute to more meaningful, strategic tasks.

AI Helps Businesses Connect With Customers Effortlessly 

When was the last time you cleared out your CRM? If you can't remember, it's likely been too long—leaving plenty of inactive records lurking, taking up space and resources that they otherwise wouldn't be with AI support.

Accurate customer information isn't just convenient for your business. It's essential. Having this information ready to go empowers your brand or org to connect with hundreds of thousands of customers in a single, simple campaign flow. Wrong information can directly inhibit sales and interaction—harming your retention and reputation in the long run.

And once your reputation is harmed online, it's very difficult to reclaim what it once was. The damage can be very difficult to repair, and take months of tireless work, if not years. Therefore, it's best to create some routines that make that damage highly unlikely.

We know these routine "cleanup" steps can be easier said than done. After all, plenty of roadblocks can come with trying to update your company address book.

These include:

• Data accuracy issues: What you find (and what customers provide) isn't always accurate. If you're using a scraper tool already to help keep you up-to-date, there's a good chance that you're (still) not getting the information you need.
  • AI solutions can help circumvent this by automating customer connections, providing seamless connectivity and up-to-date information for your business growth.
• Privacy violation risks: By trying to source this information yourself or with the help of a virtual assistant, you open yourself up to a new world of liability and risk. In our digital age, cybersecurity is more front of mind than ever, and privacy violations come with hefty legal fees.
  • Investing in an AI-drive tool helps you to navigate this across countries and GDPR/CCPA requirements—all automagically.

The Era of AI has Arrived—Are You Prepared for Transformation?

In summary, the future is not just approaching; it is here, and AI is at its forefront. Will you embrace the transformative potential of AI and position your business for unparalleled success? The choice is yours, and the opportunities that AI brings are as limitless as your willingness to explore them. It's time to embark on a journey where innovation, efficiency, and profitability converge, shaping a future where your business not only survives but thrives in the dynamic landscape of tomorrow.