Our society is always looking towards tomorrow, and then the question arises: what innovation lies there? At this point, I am sure we can all confidently say that this consists of artificial intelligence. AI involves creating smart machines, while machine learning is a way for these machines to learn from data. Together, they will transform our future by automating tasks and fostering innovation through continuous learning. These three companies are doing just that, and they are creating tomorrow’s technology. 

If you invest in these companies leading the innovative front, you will profit BIG in the coming months and years.

Machine Learning Stocks to Buy: Accenture Plc (ACN)

Accenture Plc (NYSE:ACN) specializes in consulting and information technology services. ACN has shown excessive growth and profitability in the previous year, as demonstrated by its year-over-year (YoY) Working Capital Growth of 37.11%, more than 8,000% higher than the sector median. 

ACN’s revenue was $64.58 billion over the trailing 12 months, showing an increase of 3.55% year-over-year. These metrics demonstrate how ACN’s financials continue rising, making it valuable and stable.

The machine learning industry is projected to rise by a CAGR of 37.47% from 2023-2030, reaching $188.34 billion by 2030. Reasons for this snowballing growth include digitalization and the growing demand for AI-driven solutions in varying industries. ACN is a leader in this industry; thus, as the sector’s value appreciates, so should ACN’s profits.

ACN and SandboxAQ have recently begun a partnership regarding AI and quantum computing solutions for clients to identify and amend potential cybersecurity risks. This should lead to an influx in profits and shall create brand loyalty, leading to ACN’s stock appreciating greatly.

Overall, ACN has well-versed financials and will continue growing with the machine learning industry, and with its innovative new partnership, the sky’s the limit — prompting me to give it a “buy” rating.

ServiceNow (NOW)

ServiceNow (NYSE:NOW) is a cloud computing platform using, in part, machine learning. It mainly provides a cloud-based, AI-driven platform for automating multiple management workflows in enterprises.

The global machine learning market size was valued at USD 36.73 billion in 2022 and is expected to grow at a CAGR of 34.8% from 2023 to 2030.

NOW showed its financial growth during Q3 2023. NOW reported $2.29 billion in revenue, making a YoY increase of 24.96%. Net income and diluted EPS, $242 million and $1.17, respectively, both increasing over 200% YoY. Q3 ’23 was successful for NOW overall, beating the expectations on EPS and revenue by 14.55 % and 0.65%, respectively. 

Over time, as the platform operates and gathers more data, the company becomes more proficient in predicting ways to prioritize tasks. Although it’s not being widely recognized, ServiceNow actively employs machine learning to revolutionize work processes. ServiceNow is a stock with a long runway ahead but has massive upside potential.

Machine Learning Stocks to Buy: Palantir Technologies (PLTR) 

Palantir Technologies (NYSE:PLTR) is a software company that builds foundational software solutions for large enterprises. PLTR is fully established in the market but shows signs of future growth. 

Financially, PLTR improved on nearly every metric during Q3 2023. PLTR reported $558.16 million in revenue, marking a YoY increase of 16.80%. Net income and Net profit margin also received massive surges of $71.51 million and $12.81, respectively, both increasing over 145% YoY. Overall, Q3 ’23 proved successful for PLTR, with the company beating the previous EBITDA by 186.48%. 

PLTR is set up for success through recent announcements of partnerships. The company has sizable contracts with various government agencies and a rapidly expanding list of private-sector customers. These contracts will help Palantir build up its reputation. As PLTR continues to include an emphasis on AI and machine learning, expect PLTR valuation to climb as more customers gravitate towards the company’s services.

On the date of publication, Michael Que did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

The researchers contributing to this article did not hold (either directly or indirectly) any positions in the securities mentioned in this article.