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How to leverage artificial intelligence to grow your business

In the 1960s, Joseph Weizenbaum, a computer scientist at MIT, developed a chatbot named ELIZA, which simulated human-like conversations. The program astounded users, sparking greater public interest in the potential of AI. While ELIZA’s capabilities were limited, it laid the foundation for the AI revolution we’re seeing today.

From recent breakthroughs like OpenAI’s GPT-4 to Midjourney’s image generation tool, artificial intelligence (AI) is rapidly advancing. Emerging AI tools can automate and support various business tasks, lowering costs and accelerating how quickly and efficiently humans can work—from decision-making to data analysis. Large enterprises, small-to-medium-sized businesses, and solo entrepreneurs are already using artificial intelligence. According to DigitalOcean’s May 2023 Currents survey, about 61% of businesses expect their usage of generative AI/ML to increase this year.

But before diving into using AI for your business, it’s essential to understand how this technology works, including its opportunities and challenges. In this article, we explore the benefits that businesses can gain from using AI technology, specific AI use cases that companies can implement, and considerations that come with adding this innovation to your company’s toolkit.

Artificial intelligence technologies and applications

Artificial intelligence spans diverse domains, each harnessing unique technological processes. Here’s a broad overview of prominent AI categories and their practical applications:

  • Machine learning employs algorithms to refine data performance and efficiency, impacting fields like image/speech recognition, fraud detection, autonomous vehicles, and predictive analytics.

  • Deep learning maps multi-layered neural networks for data analysis and decision-making, enhancing industries through computer vision, speech synthesis, and natural language understanding; for instance, aiding autonomous driving development.

  • Natural Language Processing (NLP) enables machines to understand and produce human language, leading to advanced applications such as chatbots, voice assistants, language translation, and content generation.

  • Robotics and automation, driven by AI, serve essential applications in industrial automation, logistics, healthcare, and drone technology, besides providing convenience via smart home systems and autonomous navigation.

  • Generative AI, a fast-growing AI subset, excels in producing digital content like images, music, text, or videos, by identifying patterns in large datasets.

Key AI use cases in business

Artificial intelligence is changing the business landscape by giving organizations high-performance tools to enhance productivity, save money, and drive revenue growth. A 2019 McKinsey study found that about 63% of businesses surveyed, who implemented AI for cost reduction and resource optimization, witnessed a revenue boost and increased ROI. From operations and sales to marketing and customer service, in this section we’ll explore some of the key AI use cases in business.

Conduct data analysis predictive sales forecasting

AI tools can rapidly process vast amounts of sales data, identifying patterns and correlations at scale that human analysts might miss, providing data-driven insights to inform strategic decisions. Additionally, through predictive analytics, these tools can forecast future sales trends based on historical data, empowering businesses to manage their resources more effectively and plan for what’s next.

A research study by Salesforce revealed that companies leveraging data for their sales and marketing efforts are more likely to witness an increase in their ROI by 15-20%. The use of AI in data analysis and sales forecasting offers businesses a competitive edge, driving efficiency and enhancing decision-making processes.

AI tools to conduct predictive sales forecasting:

  • Tableau. An advanced data visualization tool, Tableau uses AI to transform raw data into an understandable format, helping businesses identify trends and forecast sales.

  • Salesforce Einstein. As Salesforce’s AI layer, Einstein can predict sales trends based on historical data, aiding in sales forecasting and customer relationship management.

  • Akkio. An AI-driven platform, Akkio enables businesses to effortlessly build and deploy predictive models, driving data-informed decisions across a range of applications like customer churn prediction, fraud detection, and sales forecasting.

Automate tedious administrative tasks

Administrative tasks, such as data entry, scheduling, and report generation generally consume a lot of time and human resources. However, with the advent of AI, these tasks can be automated and streamlined, boosting productivity. Using machine learning algorithms, AI can learn from data patterns to enhance the accuracy and efficiency of task automation over time. Furthermore, AI-powered tools can provide real-time monitoring and alerts for administrative workflows, ensuring tasks are completed accurately and timely.

AI tools to automate administrative tasks:

  • UiPath. A popular Robotic Process Automation (RPA) platform, UiPath automates repetitive tasks across various systems and applications, reducing administrative burden.

  • Zapier. This platform automates workflows between different apps, simplifying processes like scheduling, email notifications, and data synchronization.

  • AutomationEdge. This AI-powered RPA platform automates and orchestrates business operations, aiding in process automation, IT automation, and AI-powered automation, streamlining administrative tasks.

Improve customer service and boost customer lifetime value

According to a report from Insider Intelligence and eMarketer, nearly half of the US marketers increased AI investments related to customer relationship management. From personalized interactions to functions such as predictive analytics and sentiment analysis, AI is revolutionizing the customer service sector. It’s likely that you’ve encountered AI while shopping—for instance, about 35% of purchases on Amazon were product recommendations from AI algorithms.

Businesses can leverage AI for a better customer journey and improved brand perception by taking advantage of features like AI personalization and chatbots.

AI tools to improve customer service and boost customer lifetime value:

  • Zendesk AI. Trained on billions of customer service interactions, ZenDesk AI automates responses and routes queries to the right agents, enhancing the speed and quality of customer service.

  • Intercom Fin. Intercom’s AI-driven chatbot can answer simple customer queries and route more complex ones to human agents, providing 24/7 customer service support.

  • Zoho Zia. Zoho’s AI assistant for businesses, Zia, can predict customer behavior, helping businesses tailor their interactions and get more out of their CRM.

Upgrade your corporate marketing efforts

AI tools, especially those powered by generative AI, can elevate marketing efforts by generating compelling copy, creating unique visual content, and personalizing customer interactions. From generating landing page copy to segmenting email marketing lists, artificial intelligence can help marketing teams execute their campaigns and drive customer acuqisiiton. AI tools can also provide insights into customer behavior, enabling personalized marketing, and automating routine tasks like email marketing and ad placements.

AI tools to upgrade your corporate marketing efforts:

  • Midjourney. This AI-powered tool automates the creation of visual content based on written prompts, making it easier to develop assets for campaigns, blog posts, and social media.

  • Jasper. Jasper uses the power of AI to generate marketing copy for blog posts, social media posts, email newsletters, and website copy.

  • Copy.ai. This tool employs AI to assist in creating marketing copy, ranging from blog posts to ad headlines, by providing creative suggestions and drafts.

Enhance cybersecurity and fraud detection

With the continuous evolution of the digital landscape, cyberattacks and digital fraud remain a challenge for businesses. AI tools can significantly enhance cybersecurity and fraud detection by employing machine learning algorithms to detect anomalies, predict breaches, and quickly respond to threats. They analyze large volumes of data, learning patterns, and distinguishing normal activities from suspicious ones, enabling proactive detection of potential threats.

AI tools to enhance cybersecurity and fraud detection:

  • Darktrace. This AI cybersecurity platform detects and responds to threats in real time, learning from data patterns to adapt to new and evolving threats.

  • CrowdStrike. The AI-powered endpoint protection platform provides real-time threat detection and automated incident response, preventing breaches and reducing downtime.

  • Splunk AI Ops. Splunk’s AI-offering uses machine learning to analyze big data, providing insights that can improve threat detection and response times.

AI challenges and considerations

Implementing AI in business comes with a set of challenges and considerations—from understanding the ethical and legal implications to integration and implementation of new technologies. Successfully navigating these challenges is crucial for businesses to harness AI and leverage its potential to drive innovation, efficiency, and growth.

AI hallucination and false information

While AI chatbots offer innovative solutions for interacting with customers, businesses should be aware of the potential for AI hallucination, where the model generates incorrect or nonsensical information. For instance, Google’s Bard made a false claim about the James Webb Space Telescope while OpenAI’s ChatGPT pointed lawyers towards nonexistent cases that were included in a New York federal court filing, which may result in legal sanctions for the attorneys involved.

It’s crucial to understand that these systems don’t possess a source of truth, and their output is based purely on training data, which can occasionally result in the dissemination of false information.

As businesses increasingly adopt AI technologies, it’s important to consider potential legal and ethical concerns. AI systems, particularly those utilizing machine learning, can unintentionally perpetuate biases present in their training data, leading to potentially discriminatory practices. Additionally, the use of AI in decision-making processes can raise privacy concerns and questions about accountability, particularly in sectors like healthcare and finance.

The potential misuse of AI for deceptive practices, such as deepfake creation, also poses significant ethical challenges. It’s crucial for businesses to proactively address these issues, developing robust ethical guidelines and ensuring compliance with all relevant data protection and privacy regulations when engaging with AI technology.

Workforce adaptation and training

The BDO Digital Transformation Survey has suggested that automation will create more job opportunities than it might displace, allowing the workforce to focus on strategic work. However, a widespread adoption of AI technologies would necessitate workforce adaptation, including measures such as training employees, as well as addressing concerns related to potential job displacement.

Employees need to be upskilled to effectively utilize these advanced tools and understand the implications of their use, and organizational structures may need to be adjusted to accommodate new AI-driven processes. Without adequate preparation and training, businesses risk not fully leveraging the potential benefits of AI or experiencing resistance and productivity loss.

Technology implementation and integration

Successfully deploying AI in your business operations requires careful attention to technology implementation and integration. It’s essential to ensure AI systems are compatible with existing infrastructure and that their integration doesn’t disrupt business continuity. Poorly managed implementation can lead to operational inefficiencies, unexpected costs, and the failure to achieve the anticipated benefits of AI adoption.

For example, a company wanting to employ machine learning for data analysis may need to consider aspects such as data warehousing capabilities, data privacy and security infrastructure, and the compatibility of the chosen AI tool with current data visualization or business intelligence software. Also consider your infrastructure’s ability to support AI and machine learning processes, which often require significant computing power and storage capabilities. For instance, running high-volume data analysis or training complex models requires robust server capabilities.

The future of AI in business

AI is set to have a profound impact on business in the coming years—PwC has found that AI is expected to add $15.7 trillion to the global economy by 2030. The capabilities of artificial intelligence technologies now surpass human-level performance in tasks such as object detection, sentiment analysis, and voice recognition. AI has become ubiquitous and AI systems have proliferated deep into our industrial complex—from building automobiles and conducting surgeries to engaging consumers and catching fraudsters.

But even as 77% of companies reported having either adopted or explored AI opportunities, much fewer numbers seem ideally prepared to face the cascading ethical and socio-technical risks of enterprise-wide AI adoption. According to Accenture, only 11% of surveyed risk managers feel entirely confident in assessing the potential risks associated with adopting AI across their enterprise.

The first step to maintaining the integrity of AI in the long term is acknowledging the critical role of humans in its design, operation, and use. The success of AI doesn’t just lie in its computational power, but also in the degree of human accountability, oversight, and ethical consciousness applied throughout its life cycle. Recognizing the human role in AI’s operation and use is the first stride towards its sustainable, fair, and responsible deployment.

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